Papers

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  • Preconditioned Neural Posterior Estimation for Likelihood-free Inference, X Wang, RP Kelly, DJ Warne, C Drovandi - arXiv preprint arXiv …, 2024 - arxiv.org
  • A variational neural Bayes framework for inference on intractable posterior distributions, E Maceda, EC Hector, A Lenzi, BJ Reich - arXiv preprint arXiv:2404.10899, 2024 - arxiv.org
  • Increased perceptual reliability reduces membrane potential variability in cortical neurons, B von Hünerbein, J Jordan, M Oude Lohuis… - bioRxiv, 2024 - biorxiv.org
  • How much information can be extracted from galaxy clustering at the field level?, NM Nguyen, F Schmidt, B Tucci, M Reinecke… - arXiv preprint arXiv …, 2024 - arxiv.org
  • Evolution of Analysis Techniques and Statistical Treatment, A Held - Bulletin of the American Physical Society, 2024 - APS
  • Simulation-Based Inference with Quantile Regression, H Jia - arXiv preprint arXiv:2401.02413, 2024 - arxiv.org
  • Direct Amortized Likelihood Ratio Estimation, AD Cobb, B Matejek, D Elenius, A Roy… - arXiv preprint arXiv …, 2023 - arxiv.org
  • On simulation-based inference for implicitly defined models, J Park - arXiv preprint arXiv:2311.09446, 2023 - arxiv.org
  • Machine Learning for Mechanistic Models of Metapopulation Dynamics, J Li, EL Ionides, AA King, M Pascual, N Ning - arXiv preprint arXiv …, 2023 - arxiv.org
  • Inference on spatiotemporal dynamics for networks of biological populations, J Li, EL Ionides, AA King, M Pascual, N Ning - arXiv preprint arXiv …, 2023 - arxiv.org
  • Optimal simulation-based Bayesian decisions, J Alsing, TDP Edwards, B Wandelt - arXiv preprint arXiv:2311.05742, 2023 - arxiv.org
  • Simulation based stacking, Y Yao, BRS Blancard, J Domke - arXiv preprint arXiv:2310.17009, 2023 - arxiv.org
  • Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability, M Falkiewicz, N Takeishi, I Shekhzadeh… - arXiv preprint arXiv …, 2023 - arxiv.org
  • Simulation-based Inference with the Generalized Kullback-Leibler Divergence, BK Miller, M Federici, C Weniger, P Forré - arXiv preprint arXiv …, 2023 - arxiv.org
  • Simulation-based Inference for Cardiovascular Models, A Wehenkel, J Behrmann, AC Miller, G Sapiro… - arXiv preprint arXiv …, 2023 - arxiv.org
  • Hierarchical Neural Simulation-Based Inference Over Event Ensembles, L Heinrich, S Mishra-Sharma, C Pollard… - arXiv preprint arXiv …, 2023 - arxiv.org
  • L-C2ST Local Diagnostics for Posterior Approximations in Simulation-Based Inference, J Linhart, A Gramfort, PLC Rodrigues - arXiv preprint arXiv:2306.03580, 2023 - arxiv.org
  • Learning Robust Statistics for Simulation-based Inference under Model Misspecification, D Huang, A Bharti, A Souza, L Acerbi… - arXiv preprint arXiv …, 2023 - arxiv.org
  • Generalized Bayesian Inference for Scientific Simulators via Amortized Cost Estimation, R Gao, M Deistler, JH Macke - arXiv preprint arXiv:2305.15208, 2023 - arxiv.org
  • Variational Inference with Coverage Guarantees, Y Patel, D McNamara, J Loper, J Regier… - arXiv preprint arXiv …, 2023 - arxiv.org
  • Generalised likelihood profiles for models with intractable likelihoods, DJ Warne, OJ Maclaren, EJ Carr, MJ Simpson… - arXiv preprint arXiv …, 2023 - arxiv.org
  • Neural Likelihood Surfaces for Spatial Processes with Computationally Intensive or Intractable Likelihoods, J Walchessen, A Lenzi, M Kuusela - arXiv preprint arXiv:2305.04634, 2023 - arxiv.org
  • Balancing Simulation-based Inference for Conservative Posteriors, A Delaunoy, BK Miller, P Forré, C Weniger… - arXiv preprint arXiv …, 2023 - arxiv.org
  • Statistical constraints on climate model parameters using a scalable cloud-based inference framework, J Carzon, BR de Abreu, L Regayre, K Carslaw… - arXiv preprint arXiv …, 2023 - arxiv.org
  • Accelerating Bayesian inference for stochastic epidemic models using incidence data, A Golightly, LE Wadkin, S Whitaker, A Baggaley… - arXiv preprint arXiv …, 2023 - arxiv.org
  • Sampling-Based Accuracy Testing of Posterior Estimators for General Inference, P Lemos, A Coogan, Y Hezaveh… - arXiv preprint arXiv …, 2023 - arxiv.org
  • Misspecification-robust Sequential Neural Likelihood, RP Kelly, DJ Nott, DT Frazier, DJ Warne… - arXiv preprint arXiv …, 2023 - arxiv.org
  • A Deep Learning Method for Comparing Bayesian Hierarchical Models, L Elsemüller, M Schnuerch, PC Bürkner… - arXiv preprint arXiv …, 2023 - arxiv.org
  • A simulation-based study of Zero-inflated Bernoulli model with various models for the susceptible probability, E Ali, KH Pho - arXiv preprint arXiv:2301.09698, 2023 - arxiv.org
  • Improving Effectiveness of Simulation-Based Inference in the Massively Parallel Regime, S Kulkarni, CA Moritz - IEEE Transactions on Parallel and …, 2023 - ieeexplore.ieee.org
  • Meta-Uncertainty in Bayesian Model Comparison, M Schmitt, ST Radev… - … Conference on Artificial …, 2023 - proceedings.mlr.press
  • Identification-robust inference with simulation-based pseudo-matching, B Antoine, L Khalaf, M Kichian, Z Lin - Journal of Business & …, 2023 - Taylor & Francis
  • EWF simulating exact paths of the Wright–Fisher diffusion, J Sant, PA Jenkins, J Koskela, D Spanò - Bioinformatics, 2023 - academic.oup.com
  • Distilling Importance Sampling for Likelihood Free Inference, D Prangle, C Viscardi - Journal of Computational and Graphical …, 2023 - Taylor & Francis
  • A Multi-Modal Multiple Descriptive Case Study of Graduate Students' Statistical Thinking in Statistical Tests Seven Months After Completing a Simulation-Based …, VNV Rao - 2023 - iase-web.org
  • Neural Superstatistics A Bayesian Method for Estimating Dynamic Models of Cognition, L Schumacher, PC Bürkner, A Voss, U Köthe… - arXiv preprint arXiv …, 2022 - arxiv.org
  • Validation Diagnostics for SBI algorithms based on Normalizing Flows, J Linhart, A Gramfort, PLC Rodrigues - arXiv preprint arXiv:2211.09602, 2022 - arxiv.org
  • Simulation-Based Calibration Checking for Bayesian Computation The Choice of Test Quantities Shapes Sensitivity, M Modrák, AH Moon, S Kim, P Bürkner… - arXiv preprint arXiv …, 2022 - arxiv.org
  • Truncated proposals for scalable and hassle-free simulation-based inference, M Deistler, PJ Goncalves, JH Macke - arXiv preprint arXiv:2210.04815, 2022 - arxiv.org
  • New Machine Learning Techniques for Simulation-Based Inference InferoStatic Nets, Kernel Score Estimation, and Kernel Likelihood Ratio Estimation, K Kong, KT Matchev, S Mrenna… - arXiv preprint arXiv …, 2022 - arxiv.org
  • Simulation-based inference of Bayesian hierarchical models while checking for model misspecification, F Leclercq - Physical Sciences Forum, 2022 - mdpi.com
  • Improved Marginal Unbiased Score Expansion (MUSE) via Implicit Differentiation, M Millea - arXiv preprint arXiv:2209.10512, 2022 - arxiv.org
  • Investigating the Impact of Model Misspecification in Neural Simulation-based Inference, P Cannon, D Ward, SM Schmon - arXiv preprint arXiv:2209.01845, 2022 - arxiv.org
  • Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimation, A Delaunoy, J Hermans, F Rozet, A Wehenkel… - arXiv preprint arXiv …, 2022 - arxiv.org
  • An integer grid bridge sampler for the Bayesian inference of incomplete birth-death records, L Sun, G Wei - arXiv preprint arXiv:2208.03989, 2022 - arxiv.org
  • Simulation-Based Inference with Waldo Confidence Regions by Leveraging Prediction Algorithms or Posterior Estimators for Inverse Problems, L Masserano, T Dorigo, R Izbicki, M Kuusela… - arXiv preprint arXiv …, 2022 - arxiv.org
  • Likelihood-Free Inference with Generative Neural Networks via Scoring Rule Minimization, L Pacchiardi, R Dutta - arXiv preprint arXiv:2205.15784, 2022 - arxiv.org
  • Consistent and fast inference in compartmental models of epidemics using Poisson Approximate Likelihoods, M Whitehouse, N Whiteley, L Rimella - arXiv preprint arXiv:2205.13602, 2022 - arxiv.org
  • A Flexible Bias Correction Method based on Inconsistent Estimators, Y Zhang, Y Ma, S Orso, M Karemera… - arXiv preprint arXiv …, 2022 - arxiv.org
  • Learning Optimal Test Statistics in the Presence of Nuisance Parameters, L Heinrich - arXiv preprint arXiv:2203.13079, 2022 - arxiv.org
  • GATSBI Generative Adversarial Training for Simulation-Based Inference, P Ramesh, JM Lueckmann, J Boelts… - arXiv preprint arXiv …, 2022 - arxiv.org
  • Variational methods for simulation-based inference, M Glöckler, M Deistler, JH Macke - arXiv preprint arXiv:2203.04176, 2022 - arxiv.org
  • Variational inference of fractional Brownian motion with linear computational complexity, H Verdier, F Laurent, A Cassé, CL Vestergaard… - Physical Review E, 2022 - APS
  • Towards reliable simulation-based inference, G Louppe - CAp-RFIAP 2022, 2022 - orbi.uliege.be
  • The linear template fit, D Britzger - The European Physical Journal C, 2022 - Springer
  • Simulation-based inference with approximately correct parameters via maximum entropy, R Barrett, M Ansari, G Ghoshal… - … Learning: Science and …, 2022 - iopscience.iop.org
  • Simulation-based inference proceed with caution!, G Louppe - Learning to Discover, 2022 - orbi.uliege.be
  • Simulation-based inference of reionization parameters from 3D tomographic 21 cm light-cone images, X Zhao, Y Mao, C Cheng… - The Astrophysical …, 2022 - iopscience.iop.org
  • Robust neural posterior estimation and statistical model criticism, D Ward, P Cannon, M Beaumont… - Advances in …, 2022 - proceedings.neurips.cc
  • Robust Bayesian inference for simulator-based models via the MMD posterior bootstrap, C Dellaporta, J Knoblauch… - International …, 2022 - proceedings.mlr.press
  • On the Bayesian Mixture of Generalized Linear Models with Gamma-Distributed Responses, I Susanto, N Iriawan, H Kuswanto - Econometrics, 2022 - mdpi.com
  • On Bayesian inference for the extended Plackett-Luce model, SR Johnson, DA Henderson, RJ Boys - Bayesian Analysis, 2022 - projecteuclid.org
  • Multifidelity multilevel Monte Carlo to accelerate approximate Bayesian parameter inference for partially observed stochastic processes, DJ Warne, TP Prescott, RE Baker… - Journal of Computational …, 2022 - Elsevier
  • Modern Data Science with R by Benjamin S. Baumer, Daniel T. Kaplan, and Nicholas J. Horton, Boca Raton, FL Chapman and Hall/CRC Press, 2021, 650 pp …, K Arai, V Lyubchich - 2022 - Taylor & Francis
  • Marginal unbiased score expansion and application to CMB lensing, M Millea, U Seljak - Physical Review D, 2022 - APS
  • Likelihood-based inference for partially observed epidemics on dynamic networks, F Bu, AE Aiello, J Xu, A Volfovsky - Journal of the American …, 2022 - Taylor & Francis
  • Identifiability and estimation of meta-elliptical copula generators, A Derumigny, JD Fermanian - Journal of Multivariate Analysis, 2022 - Elsevier
  • Exact simulation of max-infinitely divisible processes, P Zhong, R Huser, T Opitz - Econometrics and Statistics, 2022 - Elsevier
  • Estimation and inference for the mediation effect in a time-varying mediation model, X Cai, DL Coffman, ME Piper, R Li - BMC Medical Research Methodology, 2022 - Springer
  • Estimating the true arrival, balking, and reneging processes from censored transactional data a simulation-based approach, A Negahban - Simulation, 2022 - journals.sagepub.com
  • Efficient Bayesian inference for stochastic agent-based models, ACS Jørgensen, A Ghosh, M Sturrock… - PLoS Computational …, 2022 - journals.plos.org
  • Book Review Multivariate Data Integration Using R Methods and Applications with the mixOmics Package, by Kim-Ahn Lê Cao and Zoe Welham, Boca Raton …, S Lipovetsky - 2022 - Taylor & Francis
  • Bayesian model comparison for simulation-based inference, A Spurio Mancini, MM Docherty, MA Price… - arXiv e …, 2022 - ui.adsabs.harvard.edu
  • Approximate Bayesian Computation for Panel Data with Signature Maximum Mean Discrepancies, J Dyer, J Fitzgerald, B Rieck, SM Schmon - NeurIPS 2022 Temporal Graph … - openreview.net
  • Efficient Multifidelity Likelihood-Free Bayesian Inference with Adaptive Computational Resource Allocation, TP Prescott, DJ Warne, RE Baker - arXiv preprint arXiv:2112.11971, 2021 - arxiv.org
  • A Note on Simulation-Based Inference by Matching Random Features, C Rohilla Shalizi - arXiv e-prints, 2021 - ui.adsabs.harvard.edu
  • Reversible Gromov-Monge Sampler for Simulation-Based Inference, YH Hur, W Guo, T Liang - arXiv preprint arXiv:2109.14090, 2021 - arxiv.org
  • Nearest-Neighbor Mixture Models for Non-Gaussian Spatial Processes, X Zheng, A Kottas, B Sansó - arXiv preprint arXiv:2107.07736, 2021 - arxiv.org
  • Bayesian spatio-temporal model for high-resolution short-term forecasting of precipitation fields, SR Johnson, SE Heaps, KJ Wilson… - arXiv preprint arXiv …, 2021 - arxiv.org
  • Sequential Neural Posterior and Likelihood Approximation, S Wiqvist, J Frellsen, U Picchini - arXiv preprint arXiv:2102.06522, 2021 - arxiv.org
  • bssm Bayesian Inference of Non-linear and Non-Gaussian State Space Models in R, J Helske, M Vihola - arXiv preprint arXiv:2101.08492, 2021 - arxiv.org
  • What are the most important statistical ideas of the past 50 years?, A Gelman, A Vehtari - Journal of the American Statistical …, 2021 - Taylor & Francis
  • Truncated marginal neural ratio estimation, BK Miller, A Cole, P Forré, G Louppe… - Advances in Neural …, 2021 - proceedings.neurips.cc
  • Towards robust statistical inference for complex computer models, J Oberpriller, DR Cameron, MC Dietze… - Ecology Letters, 2021 - Wiley Online Library
  • The frontier of simulation-based inference, K Cranmer, J Brehmer… - Proceedings of the …, 2020 - National Acad Sciences
  • Small sample sizes A big data problem in high-dimensional data analysis, F Konietschke, K Schwab… - Statistical Methods in …, 2021 - journals.sagepub.com
  • Simulation-based Inference for Partially Observed Markov Process Models with Spatial Coupling, KT Asfaw - 2021 - deepblue.lib.umich.edu
  • Prediction intervals for synthetic control methods, MD Cattaneo, Y Feng, R Titiunik - Journal of the American …, 2021 - Taylor & Francis
  • Multimodel inference based on smoothed information criteria, S Zhao, X Zhang - Science China Mathematics, 2021 - Springer
  • Inference and De-noising of Non-gaussian Particle Distribution Functions A Generative Modeling Approach, J Donaghy, K Germaschewski - … , LOD 2021, Grasmere, UK, October 4–8 …, 2022 - Springer
  • Deep Signature Statistics for Likelihood-free Time-series Models, J Dyer, PW Cannon, SM Schmon - ICML Workshop on Invertible …, 2021 - openreview.net
  • Benchmarking simulation-based inference, JM Lueckmann, J Boelts, D Greenberg… - International …, 2021 - proceedings.mlr.press
  • Approximate bayesian computation for discrete spaces, IA Auzina, JM Tomczak - Entropy, 2021 - mdpi.com
  • Bridging Bayesian, frequentist and fiducial (BFF) inferences using confidence distribution, S Thornton, M Xie - arXiv preprint arXiv:2012.04464, 2020 - arxiv.org
  • Learning summary features of time series for likelihood free inference, PLC Rodrigues, A Gramfort - arXiv preprint arXiv:2012.02807, 2020 - arxiv.org
  • Generalized Posteriors in Approximate Bayesian Computation, SM Schmon, PW Cannon, J Knoblauch - arXiv preprint arXiv:2011.08644, 2020 - arxiv.org
  • Solving high-dimensional parameter inference marginal posterior densities & Moment Networks, N Jeffrey, BD Wandelt - arXiv preprint arXiv:2011.05991, 2020 - arxiv.org
  • Amortized Bayesian Inference for Models of Cognition, ST Radev, A Voss, EM Wieschen… - arXiv preprint arXiv …, 2020 - arxiv.org
  • Stable randomized generalized autoregressive conditional heteroskedastic models, JM Sampaio, PA Morettin - Econometrics and Statistics, 2020 - Elsevier
  • Spectral density-based and measure-preserving ABC for partially observed diffusion processes. An illustration on Hamiltonian SDEs, E Buckwar, M Tamborrino, I Tubikanec - Statistics and Computing, 2020 - Springer
  • Simultaneous indirect inference, impulse responses and ARMA models, L Khalaf, B Peraza López - Econometrics, 2020 - mdpi.com
  • Private posterior inference consistent with public information A case study in small area estimation from synthetic census data, J Seeman, A Slavkovic, M Reimherr - Privacy in Statistical Databases …, 2020 - Springer
  • Normality tests for dependent data large-sample and bootstrap approaches, Z Psaradakis, M Vávra - Communications in statistics-simulation …, 2020 - Taylor & Francis
  • Inference and computation with generalized additive models and their extensions, SN Wood - Test, 2020 - Springer
  • Confidence sets and hypothesis testing in a likelihood-free inference setting, N Dalmasso, R Izbicki, A Lee - International Conference on …, 2020 - proceedings.mlr.press
  • Bayesian weighted inference from surveys, D Gunawan, A Panagiotelis, W Griffiths… - Australian & New …, 2020 - Wiley Online Library
  • Simulation-Based Inference on Mixture Experiments, T Bedi - 2019 - search.proquest.com
  • Mining gold Improving simulation-based inference with latent information, J Brehmer, K Cranmer, S Mishra-Sharma… - Machine Learning and …, 2019 - orbi.uliege.be
  • M-estimators of U-processes with a change-point due to a covariate threshold, L Tan, Y Zhang - Journal of Business & Economic Statistics, 2019 - Taylor & Francis
  • High-dimensional Inferences via Estimator Augmentation Post-selection and Group Structure, S Min - 2019 - escholarship.org
  • Finite-sample inference and nonstandard asymptotics with Monte Carlo tests and R, JM Dufour, J Neves - Handbook of statistics, 2019 - Elsevier
  • Efficient sampling of conditioned Markov jump processes, A Golightly, C Sherlock - Statistics and Computing, 2019 - Springer
  • Auxiliary likelihood-based approximate Bayesian computation in state space models, GM Martin, BPM McCabe, DT Frazier… - … of Computational and …, 2019 - Taylor & Francis
  • Automatic posterior transformation for likelihood-free inference, D Greenberg, M Nonnenmacher… - … on Machine Learning, 2019 - proceedings.mlr.press
  • Simulation-based inference methods for partially observed Markov model via the R package is2, DA Doan, D Nguyen, X Dang - arXiv preprint arXiv:1811.02963, 2018 - arxiv.org
  • A Piecewise Deterministic Markov Process via $(r,θ)$ swaps in hyperspherical coordinates, A Terenin, D Thorngren - arXiv preprint arXiv:1807.00420, 2018 - arxiv.org
  • Accelerate iterated filtering, D Nguyen - arXiv preprint arXiv:1802.08613, 2018 - arxiv.org
  • Testing the equality of several multivariate normal mean vectors under heteroscedasticity A fiducial approach and an approximate test, S Eftekhar, M Sadooghi-Alvandi… - … in Statistics-Theory …, 2018 - Taylor & Francis
  • Randomization‐based statistical inference A resampling and simulation infrastructure, ID Dinov, S Palanimalai, A Khare… - Teaching statistics, 2018 - Wiley Online Library
  • Noise is not error detecting parametric heterogeneity between epidemiologic time series, EO Romero-Severson, RM Ribeiro… - Frontiers in Microbiology, 2018 - frontiersin.org
  • Gaussian process approximations for fast inference from infectious disease data, E Buckingham-Jeffery, V Isham, T House - Mathematical biosciences, 2018 - Elsevier
  • Accelerated first-order methods on the Wasserstein space for Bayesian inference, C Liu, J Zhuo, P Cheng, R Zhang, J Zhu, L Carin - stat, 2018 - researchgate.net
  • A simulation-based estimation method for bias reduction, J Fang, LJ Hong - IISE Transactions, 2018 - Taylor & Francis
  • Iterated filtering methods for Markov process epidemic models, T Stocks - arXiv preprint arXiv:1712.03058, 2017 - arxiv.org
  • Cognitive Transfer Outcomes for a Simulation-Based Introductory Statistics Curriculum, MD Beckman, RC Delmas, J Garfield - arXiv preprint arXiv:1707.06537, 2017 - arxiv.org
  • Some recent developments in statistics for spatial point patterns, J Møller, R Waagepetersen - Annual Review of Statistics and Its …, 2017 - annualreviews.org
  • Simultaneous confidence intervals for comparing several inverse Gaussian means under heteroscedasticity, M Kharrati-Kopaei, S Eftekhar - Journal of Statistical Computation …, 2017 - Taylor & Francis
  • Higher-order properties of approximate estimators, D Kristensen, B Salanié - Journal of Econometrics, 2017 - Elsevier
  • Bayesian computing with INLA a review, H Rue, A Riebler, SH Sørbye, JB Illian… - Annual Review of …, 2017 - annualreviews.org
  • Assessing the sensitivity of weighted least squares model fit indexes to local dependence in item response theory models, AC Huggins-Manley, HS Han - Structural Equation Modeling: A …, 2017 - Taylor & Francis
  • A primer on Bayesian distributional regression, N Umlauf, T Kneib - Statistical Modelling, 2018 - journals.sagepub.com
  • Simulation of multivariate diffusion bridges, M Bladt, S Finch, M Sørensen - Journal of the Royal Statistical Society …, 2016 - JSTOR
  • Simulation-based inference in a zero-inflated Bernoulli regression model, A Diop, A Diop, JF Dupuy - Communications in Statistics …, 2016 - Taylor & Francis
  • Sampling-based Inference of Time Deformation Models with Heavy Tail Distributions, Z Men, TS Wirjanto, AW Kolkiewicz - Communications in Statistics …, 2016 - Taylor & Francis
  • Which model to match?, M Barigozzi, R Halbleib, D Veredas - Available at SSRN 1986419, 2015 - papers.ssrn.com
  • NHPoisson An R package for fitting and validating nonhomogeneous Poisson processes, AC Cebrián, J Abaurrea, J Asín - Journal of Statistical Software, 2015 - jstatsoft.org
  • Minimum distance estimation of possibly noninvertible moving average models, N Gospodinov, S Ng - Journal of Business & Economic Statistics, 2015 - Taylor & Francis
  • Linear bootstrap methods for vector autoregressive moving-average models, T Jouini - Journal of Statistical Computation and Simulation, 2015 - Taylor & Francis
  • Likelihood‐based inference for discretely observed birth–death‐shift processes, with applications to evolution of mobile genetic elements, J Xu, P Guttorp, M Kato‐Maeda, VN Minin - Biometrics, 2015 - Wiley Online Library
  • Indirect estimation of randomized generalized autoregressive conditional heteroskedastic models, JM Sampaio, PA Morettin - Journal of Statistical Computation and …, 2015 - Taylor & Francis
  • A note on the simultaneous confidence intervals for the successive differences of exponential location parameters under heteroscedasticity, M Kharrati-Kopaei - Statistical Methodology, 2015 - Elsevier
  • On the equivalence of indirect inference and bootstrap bias correction for linear IV estimators, TW Chau - Economics Letters, 2014 - Elsevier
  • Multilevel structured additive regression, S Lang, N Umlauf, P Wechselberger, K Harttgen… - Statistics and …, 2014 - Springer
  • Indirect inference based on the score, P Fuleky, E Zivot - Available at SSRN 1626074, 2010 - papers.ssrn.com
  • Discussion of “The Need for More Emphasis on Prediction A 'Nondenominational'Model-Based Approach”, H Stern - The American statistician, 2014 - ncbi.nlm.nih.gov
  • Bayesian inference for hybrid discrete-continuous stochastic kinetic models, C Sherlock, A Golightly, CS Gillespie - Inverse Problems, 2014 - iopscience.iop.org
  • AABC approximate approximate Bayesian computation when simulating a large number of data sets is computationally infeasible, EO Buzbas, NA Rosenberg - arXiv preprint arXiv:1301.6282, 2013 - arxiv.org
  • The Kumaraswamy distribution median-dispersion re-parameterizations for regression modeling and simulation-based estimation, PA Mitnik, S Baek - Statistical Papers, 2013 - Springer
  • Intersection bounds Estimation and inference, V Chernozhukov, S Lee, AM Rosen - Econometrica, 2013 - Wiley Online Library
  • Discussion of 'Beyond mean regression', TG Martins, D Simpson, JB Illian, H Rue… - Statistical …, 2013 - journals.sagepub.com
  • Bayesian treed response surface models, H Chipman, EI George, RB Gramacy… - … Reviews: Data Mining …, 2013 - Wiley Online Library
  • Bayesian statistics, HS Stern - International encyclopedia of the social & behavioral …, 2015 - escholarship.org
  • Bayesian planning and inference of a progressively censored sample from linear hazard rate distribution, A Sen, N Kannan, D Kundu - Computational Statistics & Data Analysis, 2013 - Elsevier
  • Simulation-based regularized logistic regression, RB Gramacy, NG Polson - 2012 - projecteuclid.org
  • Robust inference on parameters via particle filters and sandwich covariance matrices., N Shephard, A Doucet - 2012 - ora.ox.ac.uk
  • Finite-sample bootstrap inference in GARCH models with heavy-tailed innovations, R Luger - Computational Statistics & Data Analysis, 2012 - Elsevier
  • Discrete Choice Estimator Properties for Finite Population and Simulation Sample Sizes, F Bastin, C Cirillo - Transportation research record, 2012 - journals.sagepub.com
  • Constructing summary statistics for approximate Bayesian computation semi‐automatic approximate Bayesian computation, P Fearnhead, D Prangle - Journal of the Royal Statistical …, 2012 - Wiley Online Library
  • Computationally efficient inference procedures for vast dimensional realized covariance models, L Bauwens, G Storti - Complex models and computational methods in …, 2012 - Springer
  • Modelling stochastic volatility with leverage and jumps A simulated maximum likelihood approach via particle filtering, S Malik, MK Pitt - Available at SSRN 1763783, 2011 - papers.ssrn.com
  • Using Lexis objects for multi-state models in R, B Carstensen, M Plummer - Journal of Statistical Software, 2011 - jstatsoft.org
  • Simulation-based consistent inference for biased working model of non-sparse high-dimensional linear regression, L Lin, F Li, L Zhu - Journal of statistical planning and inference, 2011 - Elsevier
  • Constructing Summary Statistics for Approximate Bayesian Computation Semi-automatic ABC, P Fearnhead, D Prangle - arXiv preprint arXiv:1004.1112, 2010 - arxiv.org
  • Simulation-Based Estimation, E Renault - Microeconometrics, 2010 - Springer
  • Non-linear regression models for Approximate Bayesian Computation, MGB Blum, O François - Statistics and computing, 2010 - Springer
  • Importance tempering, R Gramacy, R Samworth, R King - Statistics and Computing, 2010 - Springer
  • Bayesian inference in political science, finance, and marketing research, MH Chen, DK Dey, P Müller, D Sun, K Ye - … Analysis: In Honor of James O …, 2010 - Springer
  • Asymptotic models and inference for extremes of spatio-temporal data, KF Turkman, MA Amaral Turkman, JM Pereira - Extremes, 2010 - Springer
  • Simulation-based Tests for Regression Models with IID Errors Some Non-standard Cases, L Godfrey - Bootstrap Tests for Regression Models, 2009 - Springer
  • Approximate Bayesian inference in spatial generalized linear mixed models, J Eidsvik, S Martino, H Rue - Scandinavian journal of statistics, 2009 - Wiley Online Library
  • Improved small sample inference for efficient method of moments and indirect inference estimators, V Czellar, E Zivot - University of Washington, 2008 - Citeseer
  • Improved Inference for Efficient Method of Moments and Indirect Inference Estimators, V Czellar, E Zivot - 2008 - Citeseer
  • Higher Dimensional Multi-fractal Processes Filtering via Simulation, R Liu, T Lux - 2008 - Citeseer
  • Bayesian inference for clustered extremes, L Fawcett, D Walshaw - Extremes, 2008 - Springer
  • A framework for indirect inference, P Fackler, H Tastan - Unpublished. https://www. researchgate. net …, 2008 - researchgate.net
  • Simulation-based inference on the improvement in a rotatable response surface, RJ Parody, D Edwards - Quality Technology & Quantitative …, 2007 - Taylor & Francis
  • Simulation and inference for stochastic volatility models driven by Lévy processes, MPS Gander, DA Stephens - Biometrika, 2007 - academic.oup.com
  • Fitting and testing vast dimensional time-varying covariance models, RF Engle, N Shephard, K Sheppard - 2007 - papers.ssrn.com
  • Bayesian mixture modeling for spatial Poisson process intensities, with applications to extreme value analysis, A Kottas, B Sansó - Journal of Statistical Planning and Inference, 2007 - Elsevier
  • An assessment of coefficient accuracy in linear regression models with spatially varying coefficients, DC Wheeler, CA Calder - Journal of Geographical Systems, 2007 - Springer
  • Models for interval censoring and simulation-based inference for lifetime distributions, JF Lawless, D Babineau - Biometrika, 2006 - academic.oup.com
  • Likelihood-based inference for clustered line transect data, R Waagepetersen, T Schweder - Journal of Agricultural, Biological, and …, 2006 - Springer
  • Asymptotic properties of Monte Carlo estimators of diffusion processes, J Detemple, R Garcia, M Rindisbacher - Journal of Econometrics, 2006 - Elsevier
  • A Bayesian approach to modelling graphical vector autoregressions, J Corander, M Villani - Journal of Time Series Analysis, 2006 - Wiley Online Library
  • Simultaneous inference on the improvement in response surfaces, RJ Parody - 2005 - search.proquest.com
  • Simulation-based Bayesian estimation of an affine term structure model, AD Sanford, GM Martin - Computational statistics & data analysis, 2005 - Elsevier
  • Nonlinear time series nonparametric and parametric methods, J Breidt - 2005 - academia.edu
  • Multiple imputation for model checking completed‐data plots with missing and latent data, A Gelman, I Van Mechelen, G Verbeke, DF Heitjan… - …, 2005 - Wiley Online Library
  • Generalised shot noise Cox processes, J Møller, GL Torrisi - Advances in Applied Probability, 2005 - cambridge.org
  • CRAN task view Bayesian inference, JH Park, AD Martin, KM Quinn - 2005 - deepblue.lib.umich.edu
  • Spatial Cluster Modelling, N Rose - 2004 - Taylor & Francis
  • Simulation-based inference in dynamic panel probit models an application to health, P Contoyannis, AM Jones, N Rice - Empirical Economics, 2004 - Springer
  • Likelihood‐based estimation of latent generalized ARCH structures, G Fiorentini, E Sentana, N Shephard - Econometrica, 2004 - Wiley Online Library
  • Finite and Large Sample Inference for a Stochastic Volatility Model, JM Dufour, P Valéry - 2004 - academia.edu
  • Bayesian inference for mixtures of stable distributions, R Casarin - Cahier du CEREMADE, 2004 - papers.ssrn.com
  • Simulation based inference in moving average models, E Ghysels, L Khalaf, C Vodounou - Annales d'Economie et de Statistique, 2003 - JSTOR
  • Non-nested models and the likelihood ratio statistic a comparison of simulation and bootstrap based tests, G Kapetanios, M Weeks - U of London Queen Mary Economics …, 2003 - papers.ssrn.com
  • Likelihood and non‐parametric Bayesian MCMC inference for spatial point processes based on perfect simulation and path sampling, KK Berthelsen, J Møller - Scandinavian Journal of Statistics, 2003 - Wiley Online Library
  • Indirect inference, nuisance parameter, and threshold moving average models, A Guay, O Scaillet - Journal of Business & Economic Statistics, 2003 - Taylor & Francis
  • An introduction to simulation-based inference for spatial point processes, J Møller, RP Waagepetersen - Spatial statistics and computational …, 2003 - Springer
  • Simulation-Based Tests of PTM, L Khalaf, M Kichian - … Methods in Decision-Making, Economics and …, 2002 - Springer
  • Simulation-based method of moments and efficiency, M Carrasco, JP Florens - Journal of Business & Economic …, 2002 - Taylor & Francis
  • Beyond traditional statistical methods, WM Duckworth, WR Stephenson - The American Statistician, 2002 - Taylor & Francis
  • Robust simulation-based estimation of ARMA models, X de Luna, MG Genton - Journal of Computational and Graphical …, 2001 - Taylor & Francis
  • Estimating ARMA models efficiently, RA Chumacero - Studies in Nonlinear Dynamics & Econometrics, 2001 - degruyter.com
  • Alternative simulation-based estimators of logit models with random effects, G Calzolari, F Mealli, C Rampichini - 2001 - academia.edu

    • Computer Science

  • All-in-one simulation-based inference, M Gloeckler, M Deistler, C Weilbach, F Wood… - arXiv preprint arXiv …, 2024 - arxiv.org
  • Diffusion posterior sampling for simulation-based inference in tall data settings, J Linhart, GV Cardoso, A Gramfort, SL Corff… - arXiv preprint arXiv …, 2024 - arxiv.org
  • Teaching simulation-based inference Random sampling vs. random assignment? What instructors should know, B Chance, K McGaughey, S Chung… - Journal of Statistics …, 2024 - Taylor & Francis
  • Simulation-based inference for robotic grasping, N Marlier - 2024 - orbi.uliege.be
  • Fast, accurate and lightweight sequential simulation-based inference using Gaussian locally linear mappings, H Häggström, PLC Rodrigues… - arXiv preprint arXiv …, 2024 - arxiv.org
  • Point cloud transformers for parameter inference of large-scale tissue simulations, JM Herold, AH Schug, E Behle - Biophysical Journal, 2024 - cell.com
  • Simultaneous Identification of Changepoints and Model Parameters in Switching Dynamical Systems, X Fu, K Fan, H Zozmann, L Schüler, J Calabrese - bioRxiv, 2024 - biorxiv.org
  • DeepSZSim Fast Simulations of the Thermal Sunyaev-Zel'dovich Effect in Galaxy Clusters for Simulation-based Inference, E Vavagiakis, K Banker, B Zhang… - American …, 2024 - ui.adsabs.harvard.edu
  • Isolated pulsar population synthesis with simulation-based inference, V Graber, M Ronchi, C Pardo-Araujo, N Rea - arXiv preprint arXiv …, 2023 - arxiv.org
  • Inferring Atmospheric Properties of Exoplanets with Flow Matching and Neural Importance Sampling, TD Gebhard, J Wildberger, M Dax… - arXiv preprint arXiv …, 2023 - arxiv.org
  • Amortized Bayesian Decision Making for simulation-based models, M Gorecki, JH Macke, M Deistler - arXiv preprint arXiv:2312.02674, 2023 - arxiv.org
  • Loss-driven sampling within hard-to-learn areas for simulation-based neural network training, S Dymchenko, B Raffin - MLPS 2023-Machine Learning and the …, 2023 - hal.science
  • link-ancestors Fast simulation of local ancestry with tree sequence software, G Tsambos, J Kelleher, P Ralph, S Leslie, D Vukcevic - bioRxiv, 2023 - biorxiv.org
  • CHARM Creating Halos with Auto-Regressive Multi-stage networks, S Pandey, C Modi, BD Wandelt… - NeurIPS 2023 AI for …, 2023 - openreview.net
  • Hybrid SBI or How I Learned to Stop Worrying and Learn the Likelihood, C Modi, OHE Philcox - arXiv preprint arXiv:2309.10270, 2023 - arxiv.org
  • SOBER Highly Parallel Bayesian Optimization and Bayesian Quadrature over Discrete and Mixed Spaces, M Adachi, S Hayakawa, S Hamid… - ICML 2023 Workshop …, 2023 - openreview.net
  • Advancing Methods and Applicability of Simulation-Based Inference in Neuroscience, J Bölts - 2023 - tobias-lib.ub.uni-tuebingen.de
  • Amortized Neural Networks for Agent-Based Model Forecasting, D Koshelev, A Ponomarenko… - Available at SSRN …, 2023 - papers.ssrn.com
  • Compositional Score Modeling for Simulation-Based Inference, T Geffner, G Papamakarios, A Mnih - 2023 - openreview.net
  • Simultaneous identification of models and parameters of scientific simulators, C Schröder, JH Macke - arXiv preprint arXiv:2305.15174, 2023 - arxiv.org
  • Implicit representation priors meet Riemannian geometry for Bayesian robotic grasping, N Marlier, J Gustin, G Louppe, O Brüls - arXiv preprint arXiv:2304.08805, 2023 - arxiv.org
  • Simulation-based Inference for Model Parameterization on Analog Neuromorphic Hardware, J Kaiser, R Stock, E Müller, J Schemmel… - arXiv preprint arXiv …, 2023 - arxiv.org
  • Simulation-based Bayesian inference for robotic grasping, N Marlier, O Brüls, G Louppe - arXiv preprint arXiv:2303.05873, 2023 - arxiv.org
  • JANA Jointly Amortized Neural Approximation of Complex Bayesian Models, ST Radev, M Schmitt, V Pratz, U Picchini… - arXiv preprint arXiv …, 2023 - arxiv.org
  • swyft Scientific simulation-based inference at scale, B Miller, A Cole, C Weniger, F Nattino… - Astrophysics …, 2023 - ui.adsabs.harvard.edu
  • SOBER Scalable Batch Bayesian Optimization and Quadrature using Recombination Constraints, M Adachi, S Hayakawa, S Hamid, M Jørgensen… - arXiv preprint arXiv …, 2023 - arxiv.org
  • Neural networks for parameter estimation in intractable models, A Lenzi, J Bessac, J Rudi, ML Stein - Computational Statistics & Data …, 2023 - Elsevier
  • Inferring the interaction rules of complex systems with graph neural networks and approximate Bayesian computation, J Gaskell, N Campioni, JM Morales… - Journal of the …, 2023 - royalsocietypublishing.org
  • Generative Models An Interdisciplinary Perspective, K Sankaran, SP Holmes - Annual Review of Statistics and Its …, 2023 - annualreviews.org
  • GANs schön kompliziert Applications of Generative Adversarial Networks, P Ramesh - 2023 - tobias-lib.ub.uni-tuebingen.de
  • Amortized Inference with User Simulations, HS Moon, A Oulasvirta, B Lee - Proceedings of the 2023 CHI Conference …, 2023 - dl.acm.org
  • A Python-OpenCV based software for processing single-bacterium tracking microscopy videos, Z Tu, X Qin - Biophysical Journal, 2023 - cell.com
  • Maximum Likelihood Learning of Unnormalized Models for Simulation-Based Inference, P Glaser, M Arbel, A Doucet, A Gretton - arXiv preprint arXiv:2210.14756, 2022 - arxiv.org
  • Efficient Data Mosaicing with Simulation-based Inference, A Gambardella, Y Choi, D Choi, J Lee - arXiv preprint arXiv:2210.14602, 2022 - arxiv.org
  • Efficient identification of informative features in simulation-based inference, J Beck, M Deistler, Y Bernaerts… - Advances in Neural …, 2022 - proceedings.neurips.cc
  • Towards Evology a Market Ecology Agent-Based Model of US Equity Mutual Funds, A Vie, M Scholl, AM Kleinnijenhuis… - arXiv preprint arXiv …, 2022 - arxiv.org
  • Amortized Bayesian Inference of GISAXS Data with Normalizing Flows, M Zhdanov, L Randolph, T Kluge… - arXiv preprint arXiv …, 2022 - arxiv.org
  • Compositional Score Modeling for Simulation-based Inference, T Geffner, G Papamakarios, A Mnih - arXiv preprint arXiv:2209.14249, 2022 - arxiv.org
  • What simulation can do for HCI research, R Murray-Smith, A Oulasvirta, A Howes, J Müller… - Interactions, 2022 - dl.acm.org
  • Strong-lensing source reconstruction with variationally optimized Gaussian processes, K Karchev, A Coogan, C Weniger - Monthly Notices of the Royal …, 2022 - academic.oup.com
  • Speeding up inference with user simulators through policy modulation, HS Moon, S Do, W Kim, J Seo, M Chang… - Proceedings of the 2022 …, 2022 - dl.acm.org
  • Robust and integrative Bayesian neural networks for likelihood-free parameter inference, F Wrede, R Eriksson, R Jiang, L Petzold… - … Joint Conference on …, 2022 - ieeexplore.ieee.org
  • Quo vadis, agent-based modelling tools?, AJ Daly, L De Visscher, JM Baetens… - … Modelling & Software, 2022 - Elsevier
  • Probabilistic program inference in network-based epidemiological simulations, N Smedemark-Margulies, R Walters… - PLOS Computational …, 2022 - journals.plos.org
  • Probabilistic inference of simulation parameters via parallel differentiable simulation, E Heiden, CE Denniston, D Millard… - … on Robotics and …, 2022 - ieeexplore.ieee.org
  • Neural posterior domain randomization, F Muratore, T Gruner, F Wiese… - … on Robot Learning, 2022 - proceedings.mlr.press
  • Neural conditional reweighting, B Nachman, J Thaler - Physical Review D, 2022 - APS
  • Mutual information maximization for amortized likelihood inference from sampled trajectories MINIMALIST, G Isacchini, N Spisak, A Nourmohammad, T Mora… - Physical Review E, 2022 - APS
  • Learning to simulate high energy particle collisions from unlabeled data, JN Howard, S Mandt, D Whiteson, Y Yang - Scientific Reports, 2022 - nature.com
  • Inferring Articulated Rigid Body Dynamics from RGBD Video, E Heiden, Z Liu, V Vineet, E Coumans… - 2022 IEEE/RSJ …, 2022 - ieeexplore.ieee.org
  • Inference of Shape Graphs for Graph Databases, B Groz, A Lemay, S Staworko… - … on Database Theory …, 2022 - drops.dagstuhl.de
  • Estimating the impact of coordinated inauthentic behavior on content recommendations in social networks, S Mehta, R Bonneau, J Nagler, P Torr, AG Baydin - 2022 - ora.ox.ac.uk
  • Contrastive neural ratio estimation, BK Miller, C Weniger, P Forré - Advances in Neural …, 2022 - proceedings.neurips.cc
  • Bias and priors in machine learning calibrations for high energy physics, R Gambhir, B Nachman, J Thaler - Physical Review D, 2022 - APS
  • Bayesian uncertainty quantification for machine-learned models in physics, Y Gal, P Koumoutsakos, F Lanusse, G Louppe… - Nature Reviews …, 2022 - nature.com
  • Amortised likelihood-free inference for expensive time-series simulators with signatured ratio estimation, J Dyer, PW Cannon… - … Conference on Artificial …, 2022 - proceedings.mlr.press
  • AI-driven laboratory workflows enable operation in the age of social distancing, D Marescotti, C Narayanamoorthy, F Bonjour, K Kuwae… - SLAS technology, 2022 - Elsevier
  • Advances in Simulation-Based Inference Towards the automation of the Scientific Method through Learning Algorithms, J Hermans - 2022 - orbi.uliege.be
  • Accelerated Bayesian SED modeling using amortized neural posterior estimation, CH Hahn, P Melchior - The Astrophysical Journal, 2022 - iopscience.iop.org
  • A deeper look at impacts in spatial Durbin model with sphet, G Piras, P Postiglione - Geographical Analysis, 2022 - Wiley Online Library
  • A bayesian treatment of real-to-sim for deformable object manipulation, R Antonova, J Yang, P Sundaresan… - IEEE Robotics and …, 2022 - ieeexplore.ieee.org
  • Transformers Can Do Bayesian Inference, S Müller, N Hollmann, SP Arango, J Grabocka… - arXiv preprint arXiv …, 2021 - arxiv.org
  • Simulation Intelligence Towards a New Generation of Scientific Methods, A Lavin, D Krakauer, H Zenil, J Gottschlich… - arXiv preprint arXiv …, 2021 - arxiv.org
  • Group equivariant neural posterior estimation, M Dax, SR Green, J Gair, M Deistler… - arXiv preprint arXiv …, 2021 - arxiv.org
  • Arbitrary Marginal Neural Ratio Estimation for Simulation-based Inference, F Rozet, G Louppe - arXiv preprint arXiv:2110.00449, 2021 - arxiv.org
  • Simulation-based Bayesian inference for multi-fingered robotic grasping, N Marlier, O Brüls, G Louppe - arXiv preprint arXiv:2109.14275, 2021 - arxiv.org
  • Efficient State-space Exploration in Massively Parallel Simulation Based Inference, S Kulkarni, CA Moritz - arXiv preprint arXiv:2106.15508, 2021 - arxiv.org
  • Variational Likelihood-Free Gradient Descent, J Simons, S Liu, M Beaumont - Fourth Symposium on Advances in …, 2021 - openreview.net
  • Normalizing flows for likelihood-free inference with fusion simulations, CS Furia, RM Churchill - Plasma Physics and Controlled Fusion, 2022 - iopscience.iop.org
  • Neural Ratio Estimation For Simulation-based Inference, G Louppe - The 28th Nordic Conference in Mathematical Statistics, 2021 - orbi.uliege.be
  • Leveraging Global Parameters for Flow-based Neural Posterior Estimation, PLC Rodrigues, T Moreau, G Louppe… - arXiv preprint arXiv …, 2021 - hal.science
  • Learning physical properties of anomalous random walks using graph neural networks, H Verdier, M Duval, F Laurent, A Cassé… - Journal of Physics A …, 2021 - iopscience.iop.org
  • HNPE Leveraging global parameters for neural posterior estimation, P Rodrigues, T Moreau, G Louppe… - Advances in Neural …, 2021 - proceedings.neurips.cc
  • Guest Editorial ACM JETC Special Issue on Hardware-Aware Learning for Medical Applications, Y Shi, Y Liu, J Chen, S Jiang - ACM Journal on Emerging Technologies …, 2021 - dl.acm.org
  • Can Machine-Learned Summary Statistics Improve Simulation-Based Inference of Uncertain Parameters? A case study in the Upper Colorado River Basin, R Hull, E Leonarduzzi, L De la Fuente… - AGU Fall Meeting …, 2021 - ui.adsabs.harvard.edu
  • Amortized bayesian model comparison with evidential deep learning, ST Radev, M D'Alessandro, UK Mertens… - … on Neural Networks …, 2021 - ieeexplore.ieee.org
  • A quick tour of deep generative models, G Louppe - Debating the potential of machine learning in …, 2021 - orbi.uliege.be
  • Spacecraft Collision Risk Assessment with Probabilistic Programming, G Acciarini, F Pinto, S Metz, S Boufelja… - arXiv preprint arXiv …, 2020 - arxiv.org
  • Perspectives on Sim2Real Transfer for Robotics A Summary of the RSS 2020 Workshop, S Höfer, K Bekris, A Handa, JC Gamboa… - arXiv preprint arXiv …, 2020 - arxiv.org
  • Real-time parameter inference in reduced-order flame models with heteroscedastic Bayesian neural network ensembles, U Sengupta, ML Croci, MP Juniper - arXiv preprint arXiv:2011.02838, 2020 - arxiv.org
  • SBI -- A toolkit for simulation-based inference, A Tejero-Cantero, J Boelts, M Deistler… - arXiv preprint arXiv …, 2020 - arxiv.org
  • Training deep neural density estimators to identify mechanistic models of neural dynamics, PJ Gonçalves, JM Lueckmann, M Deistler… - Elife, 2020 - elifesciences.org
  • The science of deep learning, R Baraniuk, D Donoho… - Proceedings of the …, 2020 - National Acad Sciences
  • Statistical Inference via Data Science A Modern Dive Into R and the Tidyverse by Chester Ismay and Albert Y. Kim. Boca Raton, FL Chapman and Hall/CRC …, S Lipovetsky - 2020 - Taylor & Francis
  • Simulation across representation The interplay of schemas and simulation-based inference on different levels of abstraction, M Schilling, N Chang, KJ Rohlfing… - Behavioral and Brain …, 2020 - search.proquest.com
  • MSL Mining for Substructure Lenses, S Mishra-Sharma, J Brehmer… - … Source Code Library, 2020 - ui.adsabs.harvard.edu
  • Mining gold from implicit models to improve likelihood-free inference, J Brehmer, G Louppe, J Pavez… - Proceedings of the …, 2020 - National Acad Sciences
  • Combining machine learning and simulation to a hybrid modelling approach Current and future directions, L von Rueden, S Mayer, R Sifa, C Bauckhage… - Advances in Intelligent …, 2020 - Springer
  • Black-box inference for non-linear latent force models, W Ward, T Ryder, D Prangle… - … Conference on Artificial …, 2020 - proceedings.mlr.press
  • BayesFlow Learning complex stochastic models with invertible neural networks, ST Radev, UK Mertens, A Voss… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
  • Accelerating simulation-based inference with emerging AI hardware, S Kulkarni, A Tsyplikhin, MM Krell… - 2020 International …, 2020 - ieeexplore.ieee.org
  • A bayesian inference procedure based on inverse dispersion modelling for source term estimation in built-up environments, F Septier, P Armand, C Duchenne - Atmospheric Environment, 2020 - Elsevier
  • Simulation-based bias correction methods for complex models, S Guerrier, E Dupuis-Lozeron, Y Ma… - Journal of the …, 2019 - Taylor & Francis
  • PYLFIRE Python implementation of likelihood-free inference by ratio estimation, J Kokko, U Remes, O Thomas, H Pesonen… - Wellcome open …, 2019 - ncbi.nlm.nih.gov
  • Inferring catchment in internet routing, P Sermpezis, V Kotronis - Proceedings of the ACM on Measurement and …, 2019 - dl.acm.org
  • Data moves, T Erickson, M Wilkerson, W Finzer… - … Innovations in Statistics …, 2019 - escholarship.org
  • The Theory and Algorithm of Ergodic Inference, Y Zhang - arXiv preprint arXiv:1811.07192, 2018 - arxiv.org
  • Turing a language for flexible probabilistic inference, H Ge, K Xu, Z Ghahramani - International conference on …, 2018 - proceedings.mlr.press
  • The summary‐likelihood method and its implementation in the Infusion package, F Rousset, A Gouy… - Molecular ecology …, 2017 - Wiley Online Library
  • Neural nets for indirect inference, M Creel - Econometrics and Statistics, 2017 - Elsevier
  • Computational system identification of continuous-time nonlinear systems using approximate Bayesian computation, K Krishnanathan, SR Anderson… - … Journal of Systems …, 2016 - Taylor & Francis
  • Softstar Heuristic-guided probabilistic inference, M Monfort, BM Lake, B Ziebart… - Advances in Neural …, 2015 - proceedings.neurips.cc
  • Bayesian scale space analysis of temporal changes in satellite images, L Pasanen, L Holmström - Journal of Applied Statistics, 2015 - Taylor & Francis
  • Explorations in Simulation Based Techniques, MA Rahman - 2013 - search.proquest.com
  • Bayesian scale space analysis of differences in images, L Holmström, L Pasanen - Technometrics, 2012 - Taylor & Francis
  • GPU accelerated biochemical network simulation, Y Zhou, J Liepe, X Sheng, MPH Stumpf… - …, 2011 - academic.oup.com
  • From data to phenomena and back again computer-simulated signatures, E Tal - Synthese, 2011 - Springer
  • Simulation techniques for panels Efficient importance sampling, R Liesenfeld, JF Richard - The Econometrics of Panel Data: Fundamentals …, 2008 - Springer
  • Inference and evaluation of the multinomial mixture model for text clustering, L Rigouste, O Cappé, F Yvon - Information processing & management, 2007 - Elsevier
  • Bayesian analysis of image differences in multiple scales, L Holmström, L Pasanen - Proceedings, Finnish Signal …, 2007 - researchgate.net
  • Econometric software development past, present and future, M Ooms, JA Doornik - Statistica Neerlandica, 2006 - Wiley Online Library
  • Spatial point pattern analysis by using Voronoi diagrams and Delaunay tessellations–a comparative study, SN Chiu - … Journal: Journal of Mathematical Methods in …, 2003 - Wiley Online Library
  • Comparison of multiagent inference methods in multiply sectioned Bayesian networks, Y Xiang - International journal of approximate reasoning, 2003 - Elsevier
  • Efficient inference for mixed Bayesian networks, KC Chang, Z Tian - … of the Fifth International Conference on …, 2002 - ieeexplore.ieee.org

    • Astrophysics

  • Population synthesis of Galactic pulsars with machine learning, M Ronchi - arXiv preprint arXiv:2404.15953, 2024 - arxiv.org
  • KiDS-SBI Simulation-Based Inference Analysis of KiDS-1000 Cosmic Shear, M von Wietersheim-Kramsta, K Lin, N Tessore… - arXiv preprint arXiv …, 2024 - arxiv.org
  • A Strong Gravitational Lens Is Worth a Thousand Dark Matter Halos Inference on Small-Scale Structure Using Sequential Methods, S Wagner-Carena, J Lee, J Pennington… - arXiv preprint arXiv …, 2024 - arxiv.org
  • {sc SimBIG} Cosmological Constraints using Simulation-Based Inference of Galaxy Clustering with Marked Power Spectra, E Massara, CH Hahn, M Eickenberg, S Ho… - arXiv preprint arXiv …, 2024 - arxiv.org
  • Simulation-Based Inference of the sky-averaged 21-cm signal from CD-EoR with REACH, A Saxena, PD Meerburg, C Weniger, EL Acedo… - arXiv preprint arXiv …, 2024 - arxiv.org
  • Inferring astrophysical parameters using the 2D cylindrical power spectrum from reionisation, B Greig, D Prelogović, Y Qin, YS Ting… - arXiv preprint arXiv …, 2024 - arxiv.org
  • Fast likelihood-free inference in the LSS Stage IV era, GF Abellán, GC Herrera, M Martinelli… - arXiv preprint arXiv …, 2024 - arxiv.org
  • Exploring the role of the halo mass function for inferring astrophysical parameters during reionisation, B Greig, D Prelogović, J Mirocha, Y Qin, YS Ting… - arXiv preprint arXiv …, 2024 - arxiv.org
  • SIDE-real Truncated marginal neural ratio estimation for Supernova Ia Dust Extinction with real data, K Karchev, M Grayling, BM Boyd, R Trotta… - arXiv preprint arXiv …, 2024 - arxiv.org
  • Tuning neural posterior estimation for gravitational wave inference, A Kolmus, J Janquart, T Baka, T van Laarhoven… - arXiv preprint arXiv …, 2024 - arxiv.org
  • Dark Energy Survey Year 3 results likelihood-free, simulation-based $w$CDM inference with neural compression of weak-lensing map statistics, N Jeffrey, L Whiteway, M Gatti, J Williamson… - arXiv preprint arXiv …, 2024 - arxiv.org
  • Improving Convolutional Neural Networks for Cosmological Fields with Random Permutation, K Zhong, M Gatti, B Jain - arXiv preprint arXiv:2403.01368, 2024 - arxiv.org
  • Neural Simulation-Based Inference of the Neutron Star Equation of State directly from Telescope Spectra, L Brandes, C Modi, A Ghosh, D Farrell… - arXiv preprint arXiv …, 2024 - arxiv.org
  • Applying Simulation-Based Inference to Spectral and Spatial Information from the Galactic Center Gamma-Ray Excess, K Christy, EJ Baxter, J Kumar - arXiv preprint arXiv:2402.04549, 2024 - arxiv.org
  • Rapid Supernova Model Inference using Amortized Posterior Estimation, B Garretson, D Milisavljevic… - American …, 2024 - ui.adsabs.harvard.edu
  • SIMBIG Cosmological Constraints from the Redshift-Space Galaxy Skew Spectra, J Hou, AM Dizgah, CH Hahn, M Eickenberg… - arXiv preprint arXiv …, 2024 - arxiv.org
  • Simulation-based inference of deep fields galaxy population model and redshift distributions, B Moser, T Kacprzak, S Fischbacher… - arXiv preprint arXiv …, 2024 - arxiv.org
  • Simulation-Based Inference with Neural Posterior Estimation applied to X-ray spectral fitting Demonstration of working principles down to the Poisson regime, D Barret, S Dupourqué - arXiv preprint arXiv:2401.06061, 2024 - arxiv.org
  • Optimal, fast, and robust inference of reionization-era cosmology with the 21cmPIE-INN, B Schosser, C Heneka, T Plehn - arXiv preprint arXiv:2401.04174, 2024 - arxiv.org
  • A surrogate model for studying solar energetic particle transport and the seed population, AG Baydin, B Poduval, NA Schwadron - Space Weather, 2023 - Wiley Online Library
  • Learning an Effective Evolution Equation for Particle-Mesh Simulations Across Cosmologies, N Payot, P Lemos, L Perreault-Levasseur… - arXiv preprint arXiv …, 2023 - arxiv.org
  • Learning Reionization History from Quasars with Simulation-Based Inference, H Chen, J Speagle, KK Rogers - arXiv preprint arXiv:2311.16238, 2023 - arxiv.org
  • Bayesian Simulation-based Inference for Cosmological Initial Conditions, F List, NA Montel, C Weniger - arXiv preprint arXiv:2310.19910, 2023 - arxiv.org
  • SimBIG Field-level Simulation-Based Inference of Galaxy Clustering, P Lemos, L Parker, CH Hahn, S Ho… - arXiv preprint arXiv …, 2023 - arxiv.org
  • Field-level simulation-based inference with galaxy catalogs the impact of systematic effects, NSM de Santi, F Villaescusa-Navarro… - arXiv preprint arXiv …, 2023 - arxiv.org
  • Conditional Density Estimations from Privacy-Protected Data, X Xiong, NP Ju, S Zhang - arXiv preprint arXiv:2310.12781, 2023 - arxiv.org
  • Fast Parameter Inference on Pulsar Timing Arrays with Normalizing Flows, D Shih, M Freytsis, SR Taylor, JA Dror… - arXiv preprint arXiv …, 2023 - arxiv.org
  • Sensitivity-Aware Amortized Bayesian Inference, L Elsemüller, H Olischläger, M Schmitt… - arXiv preprint arXiv …, 2023 - arxiv.org
  • A forward modeling approach to analyzing galaxy clustering with SimBIG, CH Hahn, M Eickenberg, S Ho, J Hou… - Proceedings of the …, 2023 - National Acad Sciences
  • Discriminative Calibration Check Bayesian Computation from Simulations and Flexible Classifier, Y Yao, J Domke - Thirty-seventh Conference on Neural Information …, 2023 - openreview.net
  • The effect of the perturber population on subhalo measurements in strong gravitational lenses, A Coogan, N Anau Montel, K Karchev… - Monthly Notices of …, 2024 - academic.oup.com
  • Theoretical Advances in Gravitational Microlensing Guided by Artificial Intelligence, K Zhang - 2023 - search.proquest.com
  • Simulation-based Inference for Exoplanet Atmospheric Retrieval Insights from winning the Ariel Data Challenge 2023 using Normalizing Flows, M Aubin, C Cuesta-Lazaro, E Tregidga, J Viaña… - arXiv preprint arXiv …, 2023 - arxiv.org
  • Applications of Physics-Informed Machine Learning in Chemical Engineering, M Ansari - 2023 - search.proquest.com
  • Scalable inference with Autoregressive Neural Ratio Estimation, NA Montel, J Alvey, C Weniger - arXiv preprint arXiv:2308.08597, 2023 - arxiv.org
  • Flow Matching for Scalable Simulation-Based Inference, JB Wildberger, M Dax, S Buchholz… - ICML 2023 Workshop …, 2023 - openreview.net
  • Deep Learning for Simulation-based Inference, G Louppe - EDT STAT-ACTU PhD day, 2023 - orbi.uliege.be
  • Deducing Neutron Star Equation of State from Telescope Spectra with Machine-learning-derived Likelihoods, D Farrell, P Baldi, J Ott, A Ghosh, AW Steiner… - arXiv preprint arXiv …, 2023 - arxiv.org
  • The likelihood of the 21-cm power spectrum, D Prelogović, A Mesinger - arXiv preprint arXiv:2305.03074, 2023 - arxiv.org
  • The angular power spectrum of gravitational-wave transient sources as a probe of the large-scale structure, Y Zheng, N Kouvatsos, J Golomb, M Cavaglià… - arXiv preprint arXiv …, 2023 - arxiv.org
  • Reliable Simulation-Based Inference with Balanced Neural Ratio Estimation, G Louppe - NASC seminar, Pepperdine University, 2023 - orbi.uliege.be
  • SimBIG mock challenge for a forward modeling approach to galaxy clustering, CH Hahn, M Eickenberg, S Ho, J Hou… - … of Cosmology and …, 2023 - iopscience.iop.org
  • Albatross A scalable simulation-based inference pipeline for analysing stellar streams in the Milky Way, J Alvey, M Gerdes, C Weniger - arXiv preprint arXiv:2304.02032, 2023 - arxiv.org
  • Constraining the X-ray heating and reionization using 21-cm power spectra with Marginal Neural Ratio Estimation, A Saxena, A Cole, S Gazagnes, PD Meerburg… - arXiv preprint arXiv …, 2023 - arxiv.org
  • Deep Machine Learning in Cosmology Evolution or Revolution?, O Lahav - arXiv preprint arXiv:2302.04324, 2023 - arxiv.org
  • GLASS Generator for Large Scale Structure, N Tessore, A Loureiro, B Joachimi… - arXiv preprint arXiv …, 2023 - arxiv.org
  • Neural posterior estimation for exoplanetary atmospheric retrieval, M Vasist, F Rozet, O Absil, P Mollière… - arXiv preprint arXiv …, 2023 - arxiv.org
  • Debiasing Standard Siren Inference of the Hubble Constant with Marginal Neural Ratio Estimation, S Gagnon-Hartman, J Ruan… - Monthly Notices of the …, 2023 - academic.oup.com
  • Robust simulation-based inference in cosmology with Bayesian neural networks, P Lemos, M Cranmer, M Abidi, CH Hahn… - Machine Learning …, 2023 - iopscience.iop.org
  • Neural Importance Sampling for Rapid and Reliable Gravitational-Wave Inference, M Dax, SR Green, J Gair, M Pürrer, J Wildberger… - Physical Review Letters, 2023 - APS
  • Milky Way Structure Revealed by Galactic HII Regions, T Wenger, C Terrey - American Astronomical Society …, 2023 - ui.adsabs.harvard.edu
  • Modeling halo and central galaxy orientations on the SO(3) manifold with score-based generative models, Y Jagvaral, R Mandelbaum, F Lanusse - arXiv preprint arXiv:2212.05592, 2022 - arxiv.org
  • A simulation-based inference pipeline for cosmic shear with the Kilo-Degree Survey, K Lin, M von Wietersheim-Kramsta, B Joachimi… - arXiv preprint arXiv …, 2022 - arxiv.org
  • Cosmology from Galaxy Redshift Surveys with PointNet, S Anagnostidis, A Thomsen, T Kacprzak… - arXiv preprint arXiv …, 2022 - arxiv.org
  • pmwd A Differentiable Cosmological Particle-Mesh $N$-body Library, Y Li, L Lu, C Modi, D Jamieson, Y Zhang… - arXiv preprint arXiv …, 2022 - arxiv.org
  • Strong Lensing Parameter Estimation on Ground-Based Imaging Data Using Simulation-Based Inference, J Poh, A Samudre, A Ćiprijanović, B Nord… - arXiv preprint arXiv …, 2022 - arxiv.org
  • Strong-Lensing Source Reconstruction with Denoising Diffusion Restoration Models, K Karchev, NA Montel, A Coogan… - arXiv preprint arXiv …, 2022 - arxiv.org
  • Detection is truncation studying source populations with truncated marginal neural ratio estimation, N Anau Montel, C Weniger - arXiv e-prints, 2022 - ui.adsabs.harvard.edu
  • Amortized Bayesian Inference for Supernovae in the Era of the Vera Rubin Observatory Using Normalizing Flows, VA Villar - arXiv preprint arXiv:2211.04480, 2022 - arxiv.org
  • Monte Carlo Techniques for Addressing Large Errors and Missing Data in Simulation-based Inference, B Wang, J Leja, A Villar, JS Speagle - arXiv preprint arXiv:2211.03747, 2022 - arxiv.org
  • One never walks alone the effect of the perturber population on subhalo measurements in strong gravitational lenses, A Coogan, NA Montel, K Karchev, MW Grootes… - arXiv preprint arXiv …, 2022 - arxiv.org
  • Uncovering dark matter density profiles in dwarf galaxies with graph neural networks, T Nguyen, S Mishra-Sharma, R Williams, L Necib - Physical Review D, 2023 - APS
  • Estimating Cosmological Constraints from Galaxy Cluster Abundance using Simulation-Based Inference, M Reza, Y Zhang, B Nord, J Poh, A Ciprijanovic… - arXiv preprint arXiv …, 2022 - arxiv.org
  • Neural Posterior Estimation with Differentiable Simulators, J Zeghal, F Lanusse, A Boucaud, B Remy… - arXiv preprint arXiv …, 2022 - arxiv.org
  • The Cosmic Graph Optimal Information Extraction from Large-Scale Structure using Catalogues, TL Makinen, T Charnock, P Lemos… - arXiv preprint arXiv …, 2022 - arxiv.org
  • Population-Level Inference of Strong Gravitational Lenses with Neural Network-Based Selection Correction, R Legin, C Stone, Y Hezaveh… - arXiv preprint arXiv …, 2022 - arxiv.org
  • The Disordered Heterogeneous Universe Galaxy Distribution and Clustering Across Length Scales, OHE Philcox, S Torquato - Physical Review X, 2023 - APS
  • Towards reconstructing the halo clustering and halo mass function of N-body simulations using neural ratio estimation, A Dimitriou, C Weniger, CA Correa - arXiv preprint arXiv:2206.11312, 2022 - arxiv.org
  • Estimating the warm dark matter mass from strong lensing images with truncated marginal neural ratio estimation, N Anau Montel, A Coogan, C Correa… - Monthly Notices of …, 2023 - academic.oup.com
  • Un-Biasing Standard Siren Inference of the Hubble Constant, S Gagnon-Hartman, J Ruan… - American Astronomical …, 2022 - ui.adsabs.harvard.edu
  • The GIGANTES data set precision cosmology from voids in the machine-learning Era, CD Kreisch, A Pisani… - The Astrophysical …, 2022 - iopscience.iop.org
  • Snowmass2021 theory frontier white paper Astrophysical and cosmological probes of dark matter, KK Boddy, M Lisanti, SD McDermott, NL Rodd… - Journal of High Energy …, 2022 - Elsevier
  • Simulation based inference for exoplanet characterization, MV Vasist - Likelihood-free in Paris, 2022 - orbi.uliege.be
  • Reconstructing the Subhalo Mass Function from Strong Gravitational Lensing, S Wagner-Carena, R Wechsler… - APS April Meeting …, 2022 - ui.adsabs.harvard.edu
  • paltas Simulation-based inference on strong gravitational lensing systems, S Wagner-Carena, J Aalbers, S Birrer… - Astrophysics …, 2022 - ui.adsabs.harvard.edu
  • Neural simulation-based inference approach for characterizing the Galactic Center -ray excess, S Mishra-Sharma, K Cranmer - Physical Review D, 2022 - APS
  • Inferring dark matter substructure with astrometric lensing beyond the power spectrum, S Mishra-Sharma - Machine Learning: Science and Technology, 2022 - iopscience.iop.org
  • Applications of Neural Probabilistic Modeling to High Energy and Astrophysics, J Tamanas - 2022 - search.proquest.com
  • Accurate X-ray timing in the presence of systematic biases with simulation-based inference, D Huppenkothen, M Bachetti - Monthly Notices of the Royal …, 2022 - academic.oup.com
  • Simulation-Based Inference of Strong Gravitational Lensing Parameters, R Legin, Y Hezaveh, LP Levasseur… - arXiv preprint arXiv …, 2021 - arxiv.org
  • Towards constraining warm dark matter with stellar streams through neural simulation-based inference, J Hermans, N Banik, C Weniger… - Monthly Notices of …, 2021 - academic.oup.com
  • Sum of the masses of the Milky Way and M31 A likelihood-free inference approach, P Lemos, N Jeffrey, L Whiteway, O Lahav… - Physical Review D, 2021 - APS
  • Simulation-based inference of dynamical galaxy cluster masses with 3D convolutional neural networks, D Kodi Ramanah, R Wojtak… - Monthly Notices of the …, 2021 - academic.oup.com
  • Simulation-based inference for compact binaries, S Green, J Gair - APS April Meeting Abstracts, 2021 - ui.adsabs.harvard.edu
  • Role of High-Performance Computing in Heliophysics, A Bhattacharjee - AGU Fall Meeting Abstracts, 2021 - ui.adsabs.harvard.edu
  • Real-time likelihood-free inference of roman binary microlensing events with amortized neural posterior estimation, K Zhang, JS Bloom, BS Gaudi, F Lanusse… - The Astronomical …, 2021 - iopscience.iop.org
  • On the accuracy and precision of correlation functions and field-level inference in cosmology, F Leclercq, A Heavens - Monthly Notices of the Royal …, 2021 - academic.oup.com
  • Lossless, scalable implicit likelihood inference for cosmological fields, TL Makinen, T Charnock, J Alsing… - Journal of Cosmology …, 2021 - iopscience.iop.org
  • Inflation Physics from Cosmic Velocities with Joint Galaxy and CMB Simulations, M Madhavacheril - NASA ATP Proposal, 2021 - ui.adsabs.harvard.edu
  • Simulation-efficient marginal posterior estimation with swyft stop wasting your precious time, BK Miller, A Cole, G Louppe, C Weniger - arXiv preprint arXiv:2011.13951, 2020 - arxiv.org
  • Lightning-Fast Gravitational Wave Parameter Inference through Neural Amortization, A Delaunoy, A Wehenkel, T Hinderer… - arXiv preprint arXiv …, 2020 - arxiv.org
  • Automating Inference of Binary Microlensing Events with Neural Density Estimation, K Zhang, JS Bloom, BS Gaudi, F Lanusse… - arXiv preprint arXiv …, 2020 - arxiv.org
  • Primordial power spectrum and cosmology from black-box galaxy surveys, F Leclercq, W Enzi, J Jasche… - Monthly Notices of the …, 2019 - academic.oup.com
  • Mining for Dark Matter Substructure Inferring subhalo population properties from strong lenses with machine learning, J Brehmer, S Mishra-Sharma, J Hermans… - The Astrophysical …, 2019 - iopscience.iop.org
  • Approximate Bayesian computation in large-scale structure constraining the galaxy–halo connection, CH Hahn, M Vakili, K Walsh, AP Hearin… - Monthly Notices of …, 2017 - academic.oup.com

    • Mathematics

  • Simulation-based inference of black hole ringdowns in the time domain, C Pacilio, S Bhagwat, R Cotesta - arXiv preprint arXiv:2404.11373, 2024 - arxiv.org
  • Optimal Experimental Design for Bayesian Inverse Problems using Energy-Based Couplings, PC Encinar, T Schröder, AB Duncan - ICLR 2024 Workshop on …, 2024 - openreview.net
  • Consistency Models for Scalable and Fast Simulation-Based Inference, M Schmitt, V Pratz, U Köthe, PC Bürkner… - arXiv preprint arXiv …, 2023 - arxiv.org
  • Simulation-based, Finite-sample Inference for Privatized Data, J Awan, Z Wang - arXiv preprint arXiv:2303.05328, 2023 - arxiv.org
  • A practical guide to understanding and validating complex models using data simulations, GV DiRenzo, E Hanks… - Methods in Ecology and …, 2023 - Wiley Online Library
  • Variational inference for nonlinear inverse problems via neural net kernels Comparison to Bayesian neural networks, application to topology optimization, V Keshavarzzadeh, RM Kirby, A Narayan - Computer Methods in Applied …, 2022 - Elsevier
  • Simulation based inference for high dimensional inverse problems application to magnetic resonance fingerprinting, F Forbes - Colloque Intelligence Artificielle et santé: approches …, 2022 - hal.science
  • Challenges in estimation, uncertainty quantification and elicitation for pandemic modelling, B Swallow, P Birrell, J Blake, M Burgman, P Challenor… - Epidemics, 2022 - Elsevier
  • Amortised inference of fractional Brownian motion with linear computational complexity, H Verdier, F Laurent, A Cassé, C Vestergaard… - 2022 - hal.science
  • A splitting method for SDEs with locally Lipschitz drift Illustration on the FitzHugh-Nagumo model, E Buckwar, A Samson, M Tamborrino… - Applied Numerical …, 2022 - Elsevier
  • Stochastic epidemic models inference and diagnosis with Poisson random measure data augmentation, B Nguyen-Van-Yen, P Del Moral, B Cazelles - Mathematical Biosciences, 2021 - Elsevier
  • Computational skills for multivariable thinking in introductory statistics, B Adams, D Baller, B Jonas, AC Joseph… - Journal of Statistics …, 2021 - Taylor & Francis
  • A General Approach for Simulation-based Bias Correction in High Dimensional Settings, S Guerrier, M Karemera, S Orso… - arXiv preprint arXiv …, 2020 - arxiv.org
  • Differentiable likelihoods for fast inversion of'likelihood-free'dynamical systems, H Kersting, N Krämer, M Schiegg… - International …, 2020 - proceedings.mlr.press
  • Choices and trade-offs in inference with infectious disease models, S Funk, AA King - Epidemics, 2020 - Elsevier
  • Fast likelihood‐based inference for latent count models using the saddlepoint approximation, W Zhang, MV Bravington, RM Fewster - Biometrics, 2019 - Wiley Online Library
  • A Modern Look at Freedman's Box Model, DL Sun, J Alfredo - Technology Innovations in Statistics Education, 2019 - escholarship.org
  • Student gains in conceptual understanding in introductory statistics with and without a curriculum focused on simulation-based inference, B Chance, S Mendoza… - Looking Back …, 2018 - digitalcollections.dordt.edu
  • Finding Meaning in a Multivariable World A Conceptual Approach to an Algebra-Based Second Course in Statistics, K McGaughey, B Chance, NL Tintle, S Roy, T Swanson… - 2018 - digitalcollections.dordt.edu
  • Reallocating and Resampling A Comparison for Inference, K Lock Morgan - arXiv e-prints, 2017 - ui.adsabs.harvard.edu
  • The indirect method for stochastic logistic growth models, H Xuemei - Communications in Statistics-Theory and Methods, 2017 - Taylor & Francis
  • Simulated pseudo maximum likelihood identification of nonlinear models, MR Abdalmoaty, H Hjalmarsson - IFAC-PapersOnLine, 2017 - Elsevier
  • Bayesian parameter inference for stochastic SIR epidemic model with hyperbolic diffusion, A Qaffou, HE Maroufy, T Kernane - Communications in Statistics …, 2017 - Taylor & Francis
  • A second-order iterated smoothing algorithm, D Nguyen, EL Ionides - Statistics and computing, 2017 - Springer
  • Reasoning about inference using traditional and simulation-based inference models, C Case - 2016 - iase-web.org
  • Non-linear time series, K Turkman, MG Scotto, ZB Patrícia - 2016 - Springer
  • Emulation of higher-order tensors in manifold Monte Carlo methods for Bayesian inverse problems, S Lan, T Bui-Thanh, M Christie, M Girolami - Journal of Computational …, 2016 - Elsevier
  • Diagnostics for assessing the linear noise and moment closure approximations, CS Gillespie, A Golightly - Statistical Applications in Genetics and …, 2016 - degruyter.com
  • A simulated maximum likelihood method for estimation of stochastic Wiener systems, MR Abdalmoaty, H Hjalmarsson - 2016 IEEE 55th Conference …, 2016 - ieeexplore.ieee.org
  • Transdimensional approximate Bayesian computation for inference on invasive species models with latent variables of unknown dimension, OA Chkrebtii, EK Cameron, DA Campbell… - … Statistics & Data Analysis, 2015 - Elsevier
  • Inference of the transition matrix in convolved hidden Markov models and the generalized Baum–Welch algorithm, DV Lindberg, H Omre - IEEE Transactions on Geoscience and …, 2015 - ieeexplore.ieee.org
  • Delayed acceptance particle MCMC for exact inference in stochastic kinetic models, A Golightly, DA Henderson, C Sherlock - Statistics and Computing, 2015 - Springer
  • Simple simulation of diffusion bridges with application to likelihood inference for diffusions, M Bladt, M Sørensen - 2014 - projecteuclid.org
  • Contribution to the Discussion of the Paper' Geodesic Monte Carlo on Embedded Manifolds', D Simpson - Scandinavian Journal of Statistics, 2014 - JSTOR
  • Asymptotic distributions for quasi-efficient estimators in echelon VARMA models, JM Dufour, T Jouini - Computational Statistics & Data Analysis, 2014 - Elsevier
  • Toward a Bayesian Inference of Time-Deformation Models Some Simulation Studies, TS Wirjanto, Z Men - Available at SSRN 2241194, 2013 - papers.ssrn.com
  • Indirect Inference in fractional short-term interest rate diffusions, MP Laurini, LK Hotta - Mathematics and Computers in Simulation, 2013 - Elsevier
  • Folklore theorems, implicit maps, and indirect inference, PCB Phillips - Econometrica, 2012 - Wiley Online Library
  • The ensemble Kalman filter and related filters, I Myrseth, H Omre - Large‐Scale Inverse Problems and …, 2010 - Wiley Online Library
  • Stochastic volatility models, N Shephard - Macroeconometrics and Time Series Analysis, 2010 - Springer
  • Likelihood inference for unions of interacting discs, J Møller, K Helisová - Scandinavian Journal of Statistics, 2010 - Wiley Online Library
  • Likelihood-based inference for Matérn type-III repulsive point processes, ML Huber, RL Wolpert - Advances in Applied Probability, 2009 - cambridge.org
  • Inference in epidemic models without likelihoods, T McKinley, AR Cook, R Deardon - The International Journal of …, 2009 - degruyter.com
  • Exact and asymptotic tests for possibly non-regular hypotheses on stochastic volatility models, JM Dufour, P Valéry - Journal of Econometrics, 2009 - Elsevier
  • Simulation-based estimation of contingent-claims prices, PCB Phillips, J Yu - 2007 - papers.ssrn.com
  • Pseudo-likelihood estimation for discretely observed multitype Bellman–Harris branching processes, O Hyrien - Journal of statistical planning and inference, 2007 - Elsevier
  • A calibration algorithm for simulation-based pricing models, RM Reesor, DL McLeish - IMA Journal of Management …, 2007 - ieeexplore.ieee.org
  • Simulation-based approach to estimation of latent variable models, Z Qian, A Shapiro - Computational statistics & Data analysis, 2006 - Elsevier
  • Higher Dimensional Multi-Fractal Model Filtering via Simulation, R Liu, T Lux - 2006 - Citeseer
  • Book review Books about Time Series and/or Spatial Data Analysis, R Shanmugam - 2006 - Taylor & Francis
  • Spatial Statistics and Computational Methods, N Christou - Journal of Statistical Software, 2005 - jstatsoft.org
  • A stochastic model to analyze clonal data on multi‐type cell populations, O Hyrien, M Mayer‐Pröschel, M Noble, A Yakovlev - Biometrics, 2005 - Wiley Online Library
  • Normalized random measures driven by increasing additive processes, LE Nieto-Barajas, I Prünster, SG Walker - 2004 - projecteuclid.org
  • Bayesian Monte Carlo filtering for stochastic volatility models, R Casarin - Cahier du CEREMADE, 2004 - papers.ssrn.com
  • Numerical techniques for maximum likelihood estimation of continuous-time diffusion processes, GB Durham, AR Gallant - Journal of Business & Economic …, 2002 - Taylor & Francis
  • Markov chain Monte Carlo methods for stochastic volatility models, S Chib, F Nardari, N Shephard - Journal of Econometrics, 2002 - Elsevier
  • A new technique for simulating the likelihood of stochastic differential equations, J Nicolau - The Econometrics Journal, 2002 - academic.oup.com

    • Education

  • SIDE-real Supernova Ia Dust Extinction with truncated marginal neural ratio estimation applied to real data, K Karchev, M Grayling, BM Boyd… - Monthly Notices of …, 2024 - academic.oup.com
  • Pseudo-Likelihood Inference, T Gruner, B Belousov, F Muratore, D Palenicek… - arXiv preprint arXiv …, 2023 - arxiv.org
  • A point cloud approach to generative modeling for galaxy surveys at the field level, C Cuesta-Lazaro, S Mishra-Sharma - arXiv preprint arXiv:2311.17141, 2023 - arxiv.org
  • Statistical Inference for Dependence Networks in Topological Data Analysis, AB El-Yaagoubi, MK Chung, H Ombao - Frontiers in Artificial Intelligence - frontiersin.org
  • Deep Calibration of Market Simulations using Neural Density Estimators and Embedding Networks, NR Stillman, R Baggott, J Lyon, J Zhang… - Proceedings of the …, 2023 - dl.acm.org
  • Fuse It or Lose It Deep Fusion for Multimodal Simulation-Based Inference, M Schmitt, ST Radev, PC Bürkner - arXiv preprint arXiv:2311.10671, 2023 - arxiv.org
  • Simulation Based Inference of BNS Kilonova Properties A Case Study with AT2017gfo, PA Darc, CR Bom, BMO Fraga, CD Kilpatrick - arXiv preprint arXiv …, 2023 - arxiv.org
  • ADP release can explain spatially-dependent kinesin binding times, T Nguyen, BJN Reddy, SP Gross, CE Miles - bioRxiv, 2023 - biorxiv.org
  • Identifying Advantages to Teaching Linear Regression in a Modeling and Simulation Introductory Statistics Curriculum, KH Clement - 2023 - search.proquest.com
  • SBI++ Flexible, Ultra-fast Likelihood-free Inference Customized for Astronomical Applications, B Wang, J Leja, VA Villar, JS Speagle - arXiv preprint arXiv:2304.05281, 2023 - arxiv.org
  • Revealing students' stories as they construct and use a statistical model in TinkerPlots to conduct a randomization test for comparing two groups, J Noll, D Kirin, K Clement, J Dolor - Mathematical Thinking and …, 2023 - Taylor & Francis
  • Designing a large, online simulation-based introductory statistics course, EM Burnham, EE Blankenship… - Journal of Statistics and …, 2023 - Taylor & Francis
  • STUDENT PERFORMANCE IN CURRICULA CENTERED ON SIMULATION-BASED INFERENCE, B CHANCE, N TINTLE, S REYNOLDS… - Statistics Education …, 2022 - iase-web.org
  • Introducing teachers who use GUI-driven tools for the randomization test to code-driven tools, A Fergusson, M Pfannkuch - Mathematical Thinking and Learning, 2022 - Taylor & Francis
  • Student Understanding of the Hypothetical Nature of Simulations in Introductory Statistics, JM Brown - 2021 - search.proquest.com
  • Student-developed shiny applications for teaching statistics, SL Wang, AY Zhang, S Messer, A Wiesner… - Journal of Statistics …, 2021 - Taylor & Francis
  • Statistics education from a data‐centric perspective, M Gehrke, T Kistler, K Lübke, N Markgraf… - Teaching …, 2021 - Wiley Online Library
  • Factors Influencing Student Outcomes in a Large, Online Simulation-Based Introductory Statistics Course, EM Burnham - 2021 - search.proquest.com
  • Bringing visual inference to the classroom, A Loy - Journal of Statistics and Data Science Education, 2021 - Taylor & Francis
  • Why we should teach causal inference Examples in linear regression with simulated data, K Lübke, M Gehrke, J Horst… - Journal of Statistics …, 2020 - Taylor & Francis
  • Why Bayesian ideas should be introduced in the statistics curricula and how to do so, A Hoegh - Journal of Statistics Education, 2020 - Taylor & Francis
  • The CATALST curriculum A story of change, N Justice, L Le, A Sabbag, E Fry, L Ziegler… - Journal of Statistics …, 2020 - Taylor & Francis
  • Teaching introductory statistics with DataCamp, BS Baumer, AP Bray, M Çetinkaya-Rundel… - Journal of Statistics …, 2020 - Taylor & Francis
  • Development of an informal test for the fit of a probability distribution model for teaching, A Fergusson, M Pfannkuch - Journal of Statistics Education, 2020 - Taylor & Francis
  • Causal inference in introductory statistics courses, K Cummiskey, B Adams, J Pleuss… - Journal of Statistics …, 2020 - Taylor & Francis
  • Bayesian computing in the undergraduate statistics curriculum, J Albert, J Hu - Journal of Statistics Education, 2020 - Taylor & Francis
  • Toward an understanding of p-values Simulation-based inference in a traditional statistics course, C Case, M Battles, T Jacobbe - Investigations in Mathematics …, 2019 - Taylor & Francis
  • The state of statistics education research in client disciplines Themes and trends across the university, A Schwab-McCoy - Journal of Statistics Education, 2019 - Taylor & Francis
  • Statistical computing and data science in introductory statistics, K Lübke, M Gehrke, N Markgraf - … in statistical computing: From music data …, 2019 - Springer
  • Shift of Paradigm from Model-based to Simulation-based, T Ören - … , SIMULTECH 2019 Prague, Czech Republic, July 29 …, 2021 - Springer
  • Secondary teachers' understanding of statistical modeling after teaching a simulation-based statistical inference course, MD Huberty, N Justice, A Zieffler… - Looking back, looking …, 2018 - iase-web.org
  • Preservice secondary mathematics teachers' statistical knowledge A snapshot of strengths and weaknesses, JN Lovett, HS Lee - Journal of Statistics Education, 2018 - Taylor & Francis
  • … metrics of student preparation and student performance in introductory statistics Results from early data on simulation-based inference vs. nonsimulation-based …, N Tintle, J Clark, K Fischer, B Chance… - Journal of Statistics …, 2018 - Taylor & Francis
  • Implementing a simulation-based inference curriculum in Indonesia A preliminary report, KV Saputra, O Couch - … of the Tenth International Conference on …, 2018 - iase-web.org
  • Development of a tool to assess students' conceptual understanding in introductory statistics, NL Tintle, J Vander Stoep - 2018 - digitalcollections.dordt.edu
  • Developing a statistical literacy assessment for the modern introductory statistics course, L Ziegler, J Garfield - Statistics Education Research Journal, 2018 - iase-web.org
  • Comparing student success and understanding in introductory statistics under consensus and simulation-based curricula, LA Hildreth, J Robison-Cox, J Schmidt - … Education Research Journal, 2018 - iase-web.org
  • CAN A SIMULATION-BASED INFERENCE COURSE BE FLIPPED?, N Pablo, B Chance - … of the Tenth International Conference on …, 2018 - iase-web.org
  • Assessment of statistical education in Indonesia Preliminary results and initiation to simulation-based inference, KVI Saputra, L Cahyadi… - Journal of Physics …, 2018 - iopscience.iop.org
  • Assessing retention of statistical concepts after completing a post-secondary introductory statistics course, S Mendoza, S Roy - … of the Tenth International Conference on …, 2018 - iase-web.org
  • A framework to characterize student difficulties in learning inference from a simulation-based approach, C Case, T Jacobbe - Statistics Education Research Journal, 2018 - iase-web.org
  • New standards require teaching more statistics Are preservice secondary mathematics teachers ready?, JN Lovett, HS Lee - Journal of Teacher Education, 2017 - journals.sagepub.com
  • Classroom investigations of recent research concerning the hot hand phenomenon, K Ross - Journal of Statistics Education, 2017 - Taylor & Francis
  • A Study of the Effect of Using Simulations on Students' Learning of Inferential Statistics in the Elementary Statistics Classes in the Mathematics Department of the …, A Schut - 2017 - search.proquest.com
  • Student performance in curricula centered on simulation-based inference A preliminary report, B Chance, J Wong, N Tintle - Journal of Statistics Education, 2016 - Taylor & Francis
  • Comparison of learning outcomes for simulation-based and traditional inference curricula in a designed educational experiment, K Maurer, D Lock - Technology Innovations in Statistics Education, 2016 - escholarship.org
  • Broadening the Impact and Effectiveness of Simulation-Based Curricula for Introductory Statistics, NL Tintle, B Chance, G Cobb… - EnFUSE …, 2016 - digitalcollections.dordt.edu
  • Assessing the Association Between Quantitative Maturity and Student Performance in Simulation-Based and Non-Simulation Based Introductory Statistics, NL Tintle - 2016 - digitalcollections.dordt.edu
  • Simulation-Based Inference in Statistics Education Exciting Progress and Future Directions, NL Tintle - Statistics Views, 2015 - digitalcollections.dordt.edu
  • Experiencing a Paradigm Shift Teaching Statistics Through Simulation-Based Inference, NL Tintle, D Klanderman, M Maxwell - 2015 - digitalcollections.dordt.edu
  • Emphasizing the Entire Research Process Throughout the Curriculum The Next Step in Real Data Integration in Introductory Statistics Courses, NL Tintle - 2015 - digitalcollections.dordt.edu
  • Combating anti-statistical thinking using simulation-based methods throughout the undergraduate curriculum, N Tintle, B Chance, G Cobb, S Roy… - The American …, 2015 - Taylor & Francis
  • Using simulation‐based inference for learning introductory statistics, AJ Rossman, BL Chance - Wiley Interdisciplinary Reviews …, 2014 - Wiley Online Library

    • Economics

  • Fast Estimation of Bayesian State Space Models Using Amortized Simulation-Based Inference, R Khabibullin, S Seleznev - arXiv preprint arXiv:2210.07154, 2022 - arxiv.org
  • Fast Simulation-Based Bayesian Estimation of Heterogeneous and Representative Agent Models using Normalizing Flow Neural Networks, C Fen - arXiv preprint arXiv:2203.06537, 2022 - arxiv.org
  • Black-box Bayesian inference for economic agent-based models, J Dyer, P Cannon, JD Farmer, S Schmon - arXiv preprint arXiv:2202.00625, 2022 - arxiv.org
  • Evology an Empirically-Calibrated Market Ecology Agent-Based Model for Trading Strategy Search, A Vie, MP Scholl, DJ Farmer - ICML 2022 Workshop AI for Agent …, 2022 - openreview.net
  • Simple estimators and inference for higher-order stochastic volatility models, MN Ahsan, JM Dufour - Journal of Econometrics, 2021 - Elsevier
  • Likelihood-free parameter estimation for dynamic queueing networks Case study of passenger flow in an international airport terminal, A Ebert, R Dutta, K Mengersen, A Mira… - Journal of the Royal …, 2021 - academic.oup.com
  • An overview of Dynamic Model Averaging techniques in time‐series econometrics, N Nonejad - Journal of Economic Surveys, 2021 - Wiley Online Library
  • Simulated maximum likelihood estimation of agent-based models in economics and finance, J Kukacka - Network Theory and Agent-Based Modeling in …, 2019 - Springer
  • Maximum likelihood estimation of a TVP-VAR, GV Moura, MR Noriller - Economics Letters, 2019 - Elsevier
  • Detecting underestimates of risk in VaR models, S Thiele - Journal of Banking & Finance, 2019 - Elsevier
  • Moment Inequalities in the Context of Simulated and Predicted Variables, H Kaido, J Li, M Rysman - arXiv preprint arXiv:1804.03674, 2018 - arxiv.org
  • Indirect Inference with endogenously missing exogenous variables, S Chaudhuri, DT Frazier, E Renault - Journal of Econometrics, 2018 - Elsevier
  • Exit dynamics of start-up firms Structural estimation using indirect inference, R Golombek, A Raknerud - Journal of Econometrics, 2018 - Elsevier
  • Simulation-based estimation of threshold moving average models with contemporaneous shock asymmetry and an application to Turkish business cycles, H Taştan - Communications in Statistics-Simulation and …, 2017 - Taylor & Francis
  • Testing exogeneity of multinomial regressors in count data models does two-stage residual inclusion work?, A Geraci, D Fabbri, C Monfardini - Journal of Econometric Methods, 2016 - degruyter.com
  • A spatial stochastic frontier model with spillovers Evidence for Italian regions, EG Tsionas, PG Michaelides - Scottish Journal of Political …, 2016 - Wiley Online Library
  • Identification robust inference in cointegrating regressions, L Khalaf, G Urga - Journal of Econometrics, 2014 - Elsevier
  • Revisiting the FDI-led growth hypothesis The case of China, AY Yalta - Economic Modelling, 2013 - Elsevier
  • Energy consumption and economic growth in China A reconciliation, AT Yalta, H Cakar - Energy Policy, 2012 - Elsevier
  • SPECIAL ISSUE OF ECONOMETRIC THEORY ON BOOTSTRAP AND NUMERICAL METHODS IN TIME SERIES GUEST EDITORS'INTRODUCTION, AMR Taylor, TJ Vogelsang - Econometric Theory, 2011 - cambridge.org
  • Simulation‐based tests of forward‐looking models under VAR learning dynamics, L Fanelli, G Palomba - Journal of Applied Econometrics, 2011 - Wiley Online Library
  • New evidence on the FDI-led growth The case of China, AY Yalta - TOBB University of Economics and Technology …, 2011 - researchgate.net
  • Bayesian state-space estimation of stochastic volatility for storable commodities, B Karali, GJ Power, A Ishdorj - American Journal of Agricultural Economics, 2011 - JSTOR
  • Bayesian inference based only on simulated likelihood particle filter analysis of dynamic economic models, T Flury, N Shephard - Econometric Theory, 2011 - cambridge.org
  • Computational methods in econometrics, VA Hajivassiliou - Microeconometrics, 2010 - Springer
  • Bayesian estimation of stochastic-transition Markov-switching models for business cycle analysis, M Billio, R Casarin - 2010 - Citeseer
  • Simulation based selection of competing structural econometric models, T Li - Journal of Econometrics, 2009 - Elsevier
  • Cointegrating Polynomial Regressions with Power Law Trends Environmental Kuznets Curve or Omitted Time Effects?, Y Lin, H Reuvers - arXiv preprint arXiv:2009.02262, 2020 - researchgate.net
  • Identification-robust simulation-based inference in joint discrete/continuous models for energy markets, D Bolduc, L Khalaf, É Moyneur - Computational statistics & data analysis, 2008 - Elsevier
  • Evidence on simulation inference for near unit-root processes with implications for term structure estimation, GR Duffee, RH Stanton - Journal of Financial Econometrics, 2008 - academic.oup.com
  • SIMULATION BASED ECONOMETRIC METHODS Prepared for EC711, Prof. Pierre Perron, V Yankov - 2007 - Citeseer
  • Hensher, DA, Rose, JM, & Greene, WH (2005). Applied choice analysis A primer. Cambridge Cambridge University Press. 742+ xxiv pp. US $60.00. ISBN 0-521 …, TR Johnson - 2007 - search.proquest.com
  • An Objective Function for Simulation Based Inference on Exchange Rate Data, M Gilli, P Winker, V Jeleskovic - Swiss Finance Institute Research …, 2007 - papers.ssrn.com
  • Indirect inference for dynamic panel models, C Gouriéroux, PCB Phillips, J Yu - Journal of Econometrics, 2010 - Elsevier
  • Indirect Inference for Dynamic Panel Models.(2006). Research Collection School Of Economics, C Gourieroux, PCB Phillips, J Yu - 2006 - Citeseer
  • Finite-sample simulation-based inference in VAR models with application to Granger causality testing, JM Dufour, T Jouini - Journal of Econometrics, 2006 - Elsevier
  • Estimation of a simple agent-based model of financial markets An application to australian stock and foreign exchange data, S Alfarano, T Lux, F Wagner - Physica A: Statistical Mechanics and its …, 2006 - Elsevier
  • On The Specification, Identification, and Estimation of Discrete Choice Models Classical and Bayesian Perspectives, M Weeks - 2005 - Citeseer
  • Using simulation‐based inference with panel data in health economics, P Contoyannis, AM Jones… - Health Economics, 2004 - Wiley Online Library
  • Fifty years since Koyck (1954), PH Franses - Statistica Neerlandica, 2004 - Wiley Online Library
  • Relaxing the IIA assumption in locational choice models A comparison between conditional logit, mixed logit, and multinomial probit models, M Dahlberg, M Eklöf - 2003 - diva-portal.org
  • Identification, weak instruments, and statistical inference in econometrics, JM Dufour - … Journal of Economics/Revue canadienne d' …, 2003 - Wiley Online Library
  • Discrete choice methods with simulation, Kenneth E. Train, Cambridge University press, 2003, ISBN 0-521-81696-3, pp. 334, M Weeks - Journal of Applied Econometrics, 2003 - search.proquest.com
  • Bayesian analysis of a dynamic stochastic model of labor supply and saving, D Houser - Journal of Econometrics, 2003 - Elsevier
  • Computationally intensive econometrics using a distributed matrix-programming language, JA Doornik, DF Hendry… - … Transactions of the …, 2002 - royalsocietypublishing.org
  • Can We Beat the Random Walk Exchange Rate Forecasts? A Structural Approach, F Karamé, L Patureau, T Sopraseuth - … in Economics and Finance, Aix-en …, 2002 - Citeseer

    • Physics

  • A Digital Twin for Geological Carbon Storage with Controlled Injectivity, AP Gahlot, H Li, Z Yin, R Orozco… - arXiv preprint arXiv …, 2024 - arxiv.org
  • AI-powered simulation-based inference of a genuinely spatial-stochastic model of early mouse embryogenesis, MA Ramirez-Sierra, TR Sokolowski - arXiv preprint arXiv:2402.15330, 2024 - arxiv.org
  • Parameter Estimation at the LHC with Neural Simulation-Based Inference, A Ghosh - Bulletin of the American Physical Society, 2024 - APS
  • Field Level Inference of Cosmological Large Scale Structure with Neural Quantile Estimation, H Jia - Bulletin of the American Physical Society, 2024 - APS
  • Simulation-Based Inference For Pulsar Timing Arrays, J Simon - American Astronomical Society Meeting Abstracts, 2024 - ui.adsabs.harvard.edu
  • Accelerating the Next Generation of Strong Gravitational Lensing Science using Machine Learning, R Legin, A Adam, C Stone, Y Hezaveh… - American …, 2024 - ui.adsabs.harvard.edu
  • Photometric determination of main-sequence binaries with gaia, AL Wallace - Monthly Notices of the Royal Astronomical Society, 2023 - academic.oup.com
  • Simulation-Based Inference of Surface Accumulation and Basal Melt Rates of an Antarctic Ice Shelf from Isochronal Layers, G Moss, V Višnjević, O Eisen, FM Oraschewski… - arXiv preprint arXiv …, 2023 - arxiv.org
  • Photometric determination of main-sequence binaries with Gaia, AL Wallace - Monthly Notices of the Royal Astronomical Society, 2024 - academic.oup.com
  • Sensitivity Analysis of Simulation-Based Inference for Galaxy Clustering, S Pandey, C Modi, BD Wandelt, M Ho… - NeurIPS 2023 AI for …, 2023 - openreview.net
  • Simulation-based Inference of Reionization Parameters from 3D Tomographic 21 cm Light-cone Images -- II Application of Solid Harmonic Wavelet Scattering Transform, X Zhao, Y Mao, S Zuo, BD Wandelt - arXiv preprint arXiv:2310.17602, 2023 - arxiv.org
  • Conformal Contextual Robust Optimization, Y Patel, S Rayan, A Tewari - arXiv preprint arXiv:2310.10003, 2023 - arxiv.org
  • ${rm S {scriptsize IM} BIG} $ Galaxy Clustering Analysis with the Wavelet Scattering Transform, B Régaldo-Saint Blancard, CH Hahn, S Ho… - arXiv e …, 2023 - ui.adsabs.harvard.edu
  • Sequential simulation-based inference for gravitational wave signals, U Bhardwaj, J Alvey, BK Miller, S Nissanke, C Weniger - Physical Review D, 2023 - APS
  • What to do when things get crowded? Scalable joint analysis of overlapping gravitational wave signals, J Alvey, U Bhardwaj, S Nissanke, C Weniger - arXiv preprint arXiv …, 2023 - arxiv.org
  • Simulation-based inference in the search for CP violation in leptonic WH production, R Barrué, P Conde-Muíño, V Dao, R Santos - arXiv preprint arXiv …, 2023 - arxiv.org
  • Reconstructing axion-like particles from beam dumps with simulation-based inference, A Morandini, T Ferber, F Kahlhoefer - arXiv preprint arXiv:2308.01353, 2023 - arxiv.org
  • Exploring the likelihood of the 21-cm power spectrum with simulation-based inference, D Prelogović, A Mesinger - Monthly Notices of the Royal …, 2023 - academic.oup.com
  • Neural Posterior Estimation with guaranteed exact coverage the ringdown of GW150914, M Crisostomi, K Dey, E Barausse, R Trotta - arXiv preprint arXiv …, 2023 - arxiv.org
  • Scaling MadMiner with a deployment on REANA, I Espejo, S Pérez, K Hurtado, L Heinrich… - arXiv preprint arXiv …, 2023 - arxiv.org
  • Graph-informed simulation-based inference for models of active matter, NR Stillman, S Henkes, R Mayor, G Louppe - arXiv preprint arXiv …, 2023 - arxiv.org
  • Peregrine Sequential simulation-based inference for gravitational wave signals, U Bhardwaj, J Alvey, BK Miller, S Nissanke… - arXiv preprint arXiv …, 2023 - arxiv.org
  • Ultra-High-Resolution Detector Simulation with Intra-Event Aware GAN and Self-Supervised Relational Reasoning, H Hashemi, N Hartmann, S Sharifzadeh, J Kahn… - arXiv preprint arXiv …, 2023 - arxiv.org
  • Learning Electron Bunch Distribution along a FEL Beamline by Normalising Flows, A Willmann, JC Cabadağ, YY Chang, R Pausch… - arXiv preprint arXiv …, 2023 - arxiv.org
  • Simulation-based inference of single-molecule force spectroscopy, R Covino, P Cossio, L Dingeldein - Biophysical Journal, 2023 - cell.com
  • Normalizing Flows as an Avenue to Studying Overlapping Gravitational Wave Signals, J Langendorff, A Kolmus, J Janquart… - Physical Review Letters, 2023 - APS
  • j-Wave An open-source differentiable wave simulator, A Stanziola, SR Arridge, BT Cox, BE Treeby - SoftwareX, 2023 - Elsevier
  • Fluorescent single particle tracking enables high sensitivity viscometry measurements of micro-volume samples, KL Lopez, F Palomba, MA Digman - Biophysical Journal, 2023 - cell.com
  • Fluorescence lifetime analysis of smFRET with contribution of PIFE on donor and acceptor, S Jazani, T Ha - Biophysical journal, 2023 - cell.com
  • Differentiable matrix elements with madjax, L Heinrich, M Kagan - Journal of Physics: Conference Series, 2023 - iopscience.iop.org
  • Adapting to noise distribution shifts in flow-based gravitational-wave inference, J Wildberger, M Dax, SR Green, J Gair, M Pürrer… - Physical Review D, 2023 - APS
  • Quantitative Microscale Thermometry in Droplets Loaded with Gold Nanoparticles, L Sixdenier, G Baffou, C Tribet, E Marie - arXiv preprint arXiv:2209.00041, 2022 - arxiv.org
  • Solving Simulation Systematics in and with AI/ML, B Viren, J Huang, Y Huang, M Lin, Y Ren… - arXiv preprint arXiv …, 2022 - arxiv.org
  • Testing the robustness of simulation-based gravitational-wave population inference, DHT Cheung, KWK Wong, OA Hannuksela, TGF Li… - Physical Review D, 2022 - APS
  • Simulation based inference for efficient theory space sampling An application to supersymmetric explanations of the anomalous muon, L Morrison, S Profumo, N Smyth, J Tamanas - Physical Review D, 2022 - APS
  • Modeling Active Non-Markovian Oscillations, G Tucci, É Roldán, A Gambassi, R Belousov… - Physical Review Letters, 2022 - APS
  • Fast and credible likelihood-free cosmology with truncated marginal neural ratio estimation, A Cole, BK Miller, SJ Witte, MX Cai… - … of Cosmology and …, 2022 - iopscience.iop.org
  • Simulation-based inference in particle physics, J Brehmer - Nature Reviews Physics, 2021 - nature.com
  • A physics-informed, machine learning emulator of a 2d surface water model What temporal networks and simulation-based inference can help us learn about …, RM Maxwell, LE Condon, P Melchior - Water, 2021 - mdpi.com
  • Fast likelihood-free cosmology with neural density estimators and active learning, J Alsing, T Charnock, S Feeney… - Monthly Notices of the …, 2019 - academic.oup.com
  • Approximate Bayesian computation for estimating number concentrations of monodisperse nanoparticles in suspension by optical microscopy, M Röding, E Zagato, K Remaut, K Braeckmans - Physical Review E, 2016 - APS
  • Bayesian mechanistic imaging of two-dimensional heterogeneous elastic media from seismic geophysical observations, S Esmailzadeh, Z Medina-Cetina… - Frontiers in Offshore …, 2015 - search.proquest.com
  • Simulation-based inference for simultaneous processes on regular lattices, X De Luna, MG Genton - Statistics and Computing, 2002 - Springer

    • Quantitative Biology

  • Approximation of Intractable Likelihood Functions in Systems Biology via Normalizing Flows, V Zaballa, E Hui - NeurIPS 2023 Generative AI and Biology (GenBio …, 2023 - openreview.net
  • Meta-learning families of plasticity rules in recurrent spiking networks using simulation-based inference, B Confavreux, P Ramesh, PJ Goncalves… - … on Neural Information …, 2023 - openreview.net
  • Simulation-based inference for non-parametric statistical comparison of biomolecule dynamics, H Verdier, F Laurent, A Cassé… - PLOS Computational …, 2023 - journals.plos.org
  • Population Genomic Analysis of Diploid-Autopolyploid Species, M Bohutínská, J Vlček, P Monnahan, F Kolář - Polyploidy: Methods and …, 2023 - Springer
  • Generative models of morphogenesis in developmental biology, NR Stillman, R Mayor - Seminars in Cell & Developmental Biology, 2023 - Elsevier
  • DAQ-refine Protein structure model evaluation and refinement for cryo-EM maps, G Terashi, X Wang, D Kihara - Biophysical Journal, 2023 - cell.com
  • Experimental design for causal query estimation in partially observed biomolecular networks, S Mohammad-Taheri, V Tewari, R Kapre… - arXiv preprint arXiv …, 2022 - arxiv.org
  • Use of clustering to improve estimation of epidemic model parameters under a Bayesian hierarchical framework, P Alahakoon, JM McCaw, PG Taylor - medRxiv, 2022 - medrxiv.org
  • Understanding the evolution of tumours using hybrid deep generative models, TW Ouellette, P Awadalla - ICML 2022 2nd AI for Science Workshop - openreview.net
  • Simulation-based inference of differentiation trajectories from RNA velocity fields, R Gupta, D Cerletti, G Gut, A Oxenius, M Claassen - Cell Reports Methods, 2022 - Elsevier
  • Quantitative Insights into the Role of Copy Number Variants in Adaptive Evolution, G Avecilla - 2022 - search.proquest.com
  • Neural networks enable efficient and accurate simulation-based inference of evolutionary parameters from adaptation dynamics, G Avecilla, JN Chuong, F Li, G Sherlock… - PLoS …, 2022 - journals.plos.org
  • Joint analysis of microsatellites and flanking sequences enlightens complex demographic history of interspecific gene flow and vicariance in rear-edge oak …, O Lepais, A Aissi, E Véla, Y Beghami - Heredity, 2022 - nature.com
  • Inference of genome-wide processes using temporal population genomic data, A Tellier - Peer Community in Evolutionary Biology, 2022 - hal.science
  • Inference and uncertainty quantification of stochastic gene expression via synthetic models, K Öcal, MU Gutmann… - Journal of the Royal …, 2022 - royalsocietypublishing.org
  • Generative adversarial networks for construction of virtual populations of mechanistic models simulations to study Omecamtiv Mecarbil action, J Parikh, T Rumbell, X Butova, T Myachina… - … of Pharmacokinetics and …, 2022 - Springer
  • Optimal Design of Experiments for Simulation-Based Inference of Mechanistic Acyclic Biological Networks, V Zaballa, E Hui - arXiv preprint arXiv:2111.13612, 2021 - arxiv.org
  • Solving the puzzle of Fe homeostasis by integrating molecular, mathematical, and societal models, C Hodgens, BS Akpa, TA Long - Current Opinion in Plant Biology, 2021 - Elsevier
  • Futuristic methods in virus genome evolution using the Third-Generation DNA sequencing and artificial neural networks, H Shim - Global Virology III: Virology in the 21st Century, 2019 - Springer
  • Gaussian process modelling in approximate Bayesian computation to estimate horizontal gene transfer in bacteria, M Järvenpää, MU Gutmann, A Vehtari… - The Annals of Applied …, 2018 - JSTOR
  • An efficient moments-based inference method for within-host bacterial infection dynamics, DJ Price, A Breuzé, R Dybowski… - PLOS Computational …, 2017 - journals.plos.org
  • Iterated Filtering and Smoothing with Application to Infectious Disease Models., DX Nguyen - 2016 - deepblue.lib.umich.edu
  • Recombination produces coherent bacterial species clusters in both core and accessory genomes, P Marttinen, NJ Croucher, MU Gutmann… - Microbial …, 2015 - ncbi.nlm.nih.gov
  • Approximating the dynamics of the Hybrid Stochastic-Deterministic Apoptosis pathway, SK Palaniappan, F Bertaux, M Pichene, E Fabre, G Batt… - CMSB 2015, 2015 - hal.science
  • AABC approximate approximate Bayesian computation for inference in population-genetic models, EO Buzbas, NA Rosenberg - Theoretical population biology, 2015 - Elsevier
  • Research Article Integrative Genomics with Mediation Analysis in a Survival Context, S Nemes, TZ Parris, A Danielsson, Z Einbeigi… - 2013 - academia.edu
  • Microsatellites as targets of natural selection, RJ Haasl, BA Payseur - Molecular biology and evolution, 2012 - academic.oup.com
  • Cell motility models and inference for dynamic systems or Plug-and-play inference What? Why? When? How?, E Ionides - 2012 - Citeseer
  • Inferring the demographic history of African farmers and Pygmy hunter–gatherers using a multilocus resequencing data set, E Patin, G Laval, LB Barreiro, A Salas, O Semino… - PLoS …, 2009 - journals.plos.org
  • Bayesian hidden Markov modeling of array CGH data, S Guha, Y Li, D Neuberg - Journal of the American Statistical …, 2008 - Taylor & Francis
  • A statistical framework for the analysis of multivariate infectious disease surveillance counts, L Held, M Höhle, M Hofmann - Statistical modelling, 2005 - journals.sagepub.com

    • Neuroscience

  • Simulation-based inference using surjective sequential neural likelihood estimation, S Dirmeier, C Albert, F Perez-Cruz - arXiv preprint arXiv:2308.01054, 2023 - arxiv.org
  • Methods and considerations for estimating parameters in biophysically detailed neural models with simulation based inference, N Tolley, PLC Rodrigues, A Gramfort, SR Jones - bioRxiv, 2023 - biorxiv.org
  • Amortized Bayesian inference on generative dynamical network models of epilepsy using deep neural density estimators, M Hashemi, AN Vattikonda, J Jha, V Sip… - Neural Networks, 2023 - Elsevier
  • Combined statistical-mechanistic modeling links ion channel genes to physiology of cortical neuron types, Y Bernaerts, M Deistler, PJ Goncalves, J Beck… - bioRxiv, 2023 - biorxiv.org
  • Bayesian Inference of a Spectral Graph Model for Brain Oscillations, H Jin, P Verma, F Jiang, S Nagarajan, A Raj - bioRxiv, 2023 - biorxiv.org
  • Recurrent connectivity structure controls the emergence of co-tuned excitation and inhibition, E Giannakakis, O Vinogradov, V Buendia, A Levina - bioRxiv, 2023 - biorxiv.org
  • Simulation-based inference for efficient identification of generative models in connectomics, J Boelts, P Harth, R Gao, D Udvary, F Yanez, D Baum… - bioRxiv, 2023 - biorxiv.org
  • Personalized virtual brains of Alzheimer's Disease link dynamical biomarkers of fMRI with increased local excitability, BH Yalcinkaya, A Ziaeemehr, J Fousek, M Hashemi… - medRxiv, 2023 - medrxiv.org
  • Inferring Pyramidal Neuron Morphology using EAP Data, Z Chen, M Carroll, SS Nair - 2023 11th International IEEE …, 2023 - ieeexplore.ieee.org
  • A general integrative neurocognitive modeling framework to jointly describe EEG and decision-making on single trials, A Ghaderi-Kangavari, JA Rad, MD Nunez - Computational Brain & …, 2023 - Springer
  • The virtual aging brain a model-driven explanation for cognitive decline in older subjects, M Lavanga, J Stumme, BH Yalcinkaya, J Fousek… - bioRxiv, 2022 - biorxiv.org
  • Simulation-Based Inference for Whole-Brain Network Modeling of Epilepsy using Deep Neural Density Estimators, M Hashemi, AN Vattikonda, J Jha, V Sip… - medRxiv, 2022 - medrxiv.org
  • Simulation-Based Inference for Neuroscience and Beyond, JM Lückmann - 2022 - tobias-lib.ub.uni-tuebingen.de
  • Neuro-symbolic neurodegenerative disease modeling as probabilistic programmed deep kernels, A Lavin - AI for Disease Surveillance and Pandemic Intelligence …, 2022 - Springer
  • Neural Posterior Estimation of hierarchical models in neuroscience, J Linhart, PLC Rodrigues, T Moreau… - … de Traitement du …, 2022 - hal.science
  • Fast inference of spinal neuromodulation for motor control using amortized neural networks, LN Govindarajan, JS Calvert, SR Parker… - Journal of Neural …, 2022 - iopscience.iop.org
  • Neural empirical bayes Source distribution estimation and its applications to simulation-based inference, M Vandegar, M Kagan, A Wehenkel… - International …, 2021 - proceedings.mlr.press
  • Interrogating theoretical models of neural computation with emergent property inference, SR Bittner, A Palmigiano, AT Piet, CA Duan, CD Brody… - Elife, 2021 - elifesciences.org
  • Inferring Morphology of a Neuron from In Vivo LFP Data, Z Chen, D Dopp, SS Nair… - 2021 10th International …, 2021 - ieeexplore.ieee.org
  • Eye-region specific ribbon tuning supports distinct modes of synaptic transmission in same-type cone-photoreceptors, C Schröder, J Oesterle, P Berens, T Yoshimatsu… - bioRxiv, 2021 - biorxiv.org
  • Distinct synaptic transfer functions in same-type photoreceptors, C Schröder, J Oesterle, P Berens, T Yoshimatsu… - Elife, 2021 - elifesciences.org
  • An Efficient Pipeline for Biophysical Modeling of Neurons, N Opsal, P Canfield, T Banks… - 2021 10th International …, 2021 - ieeexplore.ieee.org
  • Understanding Cortical Neuron Dynamics Through Simulation-Based Applications of Machine Learning, R Haynes - 2020 - search.proquest.com
  • Bayesian inference for biophysical neuron models enables stimulus optimization for retinal neuroprosthetics, J Oesterle, C Behrens, C Schröder, T Hermann, T Euler… - Elife, 2020 - elifesciences.org
  • Comparing neural simulations by neural density estimation, J Boelts, JM Lueckmann, PJ Goncalves… - 2019 Conference on … - researchgate.net
  • A parametric approach to voxel-based meta-analysis, SG Costafreda, AS David, MJ Brammer - Neuroimage, 2009 - Elsevier
  • Fully automatic determination of morphological parameters of proximal femur from calibrated fluoroscopic images through particle filtering, X Dong, G Zheng - Image Analysis and Recognition: Third International …, 2006 - Springer

    • Quantitative Finance

  • Stock return predictability Evidence across US industries, QTT Pham - Finance Research Letters, 2021 - Elsevier
  • Empirical asset pricing with multi-period disaster risk A simulation-based approach, J Sönksen, J Grammig - Journal of Econometrics, 2021 - Elsevier
  • Identification of social interaction effects in financial data, TS Jang - Computational Economics, 2015 - Springer
  • Tail dependence of financial stocks and CDS markets–Evidence using copula methods and simulation-based inference, PP Da Silva, PT Rebelo, C Afonso - Economics, 2014 - degruyter.com
  • Macroeconomic determinants of stock volatility and volatility premiums, V Corradi, W Distaso, A Mele - Journal of Monetary Economics, 2013 - Elsevier
  • Correcting estimation bias in dynamic term structure models, MD Bauer, GD Rudebusch, JC Wu - Journal of Business & …, 2012 - Taylor & Francis
  • Capital structure The case of firms issuing debt, Y Zhu - Australian Journal of Management, 2012 - journals.sagepub.com
  • Bayesian inference in a stochastic volatility Nelson–Siegel model, N Hautsch, F Yang - Computational Statistics & Data Analysis, 2012 - Elsevier
  • Simulation-based estimation methods for financial time series models, J Yu - Handbook of Computational Finance, 2011 - Springer
  • Does the currency regime shape unhedged currency exposure?, I Patnaik, A Shah - Journal of International Money and Finance, 2010 - Elsevier
  • A model of limit-order book dynamics and a consistent estimation procedure, L Zhao - 2010 - search.proquest.com
  • Stochastic volatility origins and overview, N Shephard, TG Andersen - Handbook of financial time series, 2009 - Springer
  • Moment–based estimation of stochastic volatility models, E Renault - Handbook of Financial Time Series, 2009 - Springer
  • Maximum likelihood and Gaussian estimation of continuous time models in finance, PCB Phillips, J Yu - Handbook of financial time series, 2009 - Springer
  • Simulation-Based Estimation of Contingent-Claims Prices.(2006). Research Collection School Of Economics, PCB Phillips, J Yu - 2006 - Citeseer
  • Stochastic Volatility., N Shephard - 2005 - ora.ox.ac.uk
  • Simulation methods for nonlinear and non-Gaussian models in finance, R Casarin - Premio SIE, Rivista Italiana degli Economisti, 2005 - Citeseer
  • Exact multivariate tests of asset pricing models with stable asymmetric distributions, MC Beaulieu, JM Dufour, L Khalaf - 2005 - Springer
  • Modelling and forecasting financial data techniques of nonlinear dynamics, ZQJ Lu - 2004 - Taylor & Francis
  • Kernel-based indirect inference, M Billio, A Monfort - Journal of Financial Econometrics, 2003 - academic.oup.com
  • MCMC analysis of diffusion models with application to finance, B Eraker - Journal of Business & Economic Statistics, 2001 - Taylor & Francis

    • Astronomy

  • SB-ETAS using simulation based inference for scalable, likelihood-free inference for the ETAS model of earthquake occurrences, S Stockman, DJ Lawson, MJ Werner - arXiv preprint arXiv:2404.16590, 2024 - arxiv.org
  • Inferring galaxy cluster masses from cosmic microwave background lensing with neural simulation based inference, EJ Baxter, S Pandey - arXiv preprint arXiv:2401.08910, 2024 - arxiv.org
  • Characterization of Microservice Response Time in Kubernetes A Mixture Density Network Approach, L Manca, D Borsatti, F Poltronieri… - … on Network and …, 2023 - ieeexplore.ieee.org
  • PEREGRINE Gravitational wave parameter inference with neural ration estimation, U Bhardwaj, J Alvey, BK Miller… - Astrophysics …, 2023 - ui.adsabs.harvard.edu
  • A transport approach to sequential simulation-based inference, PB Rubio, Y Marzouk, M Parno - arXiv preprint arXiv:2308.13940, 2023 - arxiv.org
  • Fast emulation of anisotropies induced in the cosmic microwave background by cosmic strings, MA Price, M Mars, MM Docherty, AS Mancini… - arXiv preprint arXiv …, 2023 - arxiv.org
  • Albatross Stellar stream parameter inference with neural ratio estimation, J Alvey, M Gerdes, C Weniger - Astrophysics Source Code …, 2023 - ui.adsabs.harvard.edu
  • ERGO-ML Towards a robust machine learning model for inferring the fraction of accreted stars in galaxies from integral-field spectroscopic maps, E Angeloudi, J Falcón-Barroso… - Monthly Notices of …, 2023 - academic.oup.com
  • From Images to Dark Matter End-To-End Inference of Substructure From Hundreds of Strong Gravitational Lenses, S Wagner-Carena, J Aalbers, S Birrer… - The Astrophysical …, 2023 - iopscience.iop.org
  • Emulating hydrodynamic simulations with semi-analytic modeling comparing the evolution of global quantities in the Santa Cruz SAM and IllustrisTNG, A Gabrielpillai, R Somerville, S Genel… - American …, 2023 - ui.adsabs.harvard.edu
  • Deducing neutron star equation of state parameters directly from telescope spectra with uncertainty-aware machine learning, D Farrell, P Baldi, J Ott, A Ghosh… - … of Cosmology and …, 2023 - iopscience.iop.org
  • Cold gas mass measurements for the era of large optical spectroscopic surveys, D Scholte, A Saintonge - Monthly Notices of the Royal …, 2023 - academic.oup.com
  • A probabilistic deep learning model to distinguish cusps and cores in dwarf galaxies, J Expósito-Márquez, CB Brook… - Monthly Notices of …, 2023 - academic.oup.com
  • Single frequency CMB B-mode inference with realistic foregrounds from a single training image, N Jeffrey, F Boulanger, BD Wandelt… - Monthly Notices of …, 2022 - academic.oup.com
  • Microlensing model inference with normalising flows and reversible jump MCMC, D Keehan, J Yarndley, N Rattenbury - Astronomy and Computing, 2022 - Elsevier
  • DIGS deep inference of galaxy spectra with neural posterior estimation, G Khullar, B Nord, A Ćiprijanović… - … Learning: Science and …, 2022 - iopscience.iop.org
  • Cosmic shear cosmology beyond two-point statistics a combined peak count and correlation function analysis of DES-Y1, J Harnois-Déraps, N Martinet, T Castro… - Monthly Notices of …, 2021 - academic.oup.com
  • Probing Dark Matter Substructure with Stellar Streams and Neural Simulation-Based Inference, J Hermans, N Banik, C Weniger, G Bertone… - Machine Learning and …, 2020 - orbi.uliege.be

    • Engineering

  • Structural Model Updating and Model Selection Bayesian Inference Approach Based on Simulation, A Ben Abdessalem - International Conference of Steel and Composite for …, 2024 - Springer
  • Inferring Binary Properties from Gravitational Wave Signals, J Roulet, T Venumadhav - arXiv preprint arXiv:2402.11439, 2024 - arxiv.org
  • Amortized identification of biomolecular conformations in Cryo-EM using simulation-based inference, L Dingeldein, D Silva-Sánchez, E Dimprima… - Biophysical …, 2024 - cell.com
  • Simulation‐based inference for reliability model selection and parameter calibration An application to fatigue, A Ben Abdessalem - Quality and Reliability Engineering …, 2024 - Wiley Online Library
  • Learning fire spread dynamics with physics-constrained machine learning, J Buch, A Jivani, X Huan, AP Williams, P Gentine - Bulletin of the American …, 2023 - APS
  • Driver-Pedestrian Perceptual Models Demonstrate Coupling Implications for Vehicle Automation, JE Domeyer, JD Lee, H Toyoda… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
  • Data-centric Engineering Integrating simulation, machine learning and statistics. Challenges and opportunities, I Pan, LR Mason, OK Matar - Chemical Engineering Science, 2022 - Elsevier
  • A simulation-based Bayesian approach to predict the distribution of maximum pit depth in steam generator tubes, I Hazra, MD Pandey - Nuclear Engineering and Design, 2022 - Elsevier
  • Toward Vehicle Automation that Communicates and Coordinates Understanding Road User Behavior, JE Domeyer - 2021 - search.proquest.com
  • Simulation-based engineering design solving parameter inference and multi-objective optimization problems on a shared simulation budget, OPH Jones, JE Oakley… - 2021 IEEE International …, 2021 - ieeexplore.ieee.org
  • Identification of Vehicle Dynamics Parameters Using Simulation-based Inference, A Boyali, S Thompson, DR Wong - 2021 IEEE Intelligent …, 2021 - ieeexplore.ieee.org
  • A scalable energy modeling framework for electric vehicles in regional transportation networks, X Xu, HMA Aziz, H Liu, MO Rodgers, R Guensler - Applied Energy, 2020 - Elsevier
  • Simulation-based estimation of the real demand in bike-sharing systems in the presence of censoring, A Negahban - European Journal of Operational Research, 2019 - Elsevier
  • Reverse engineering under uncertainty, P Kirk, D Silk, MPH Stumpf - Uncertainty in Biology: A Computational …, 2016 - Springer

    • Genetics

  • Parameter Inference for Stochastic Models of Gene Expression in Eukaryotic Cells, A Siddiqui - 2023 - diva-portal.org
  • Recommendations for improving statistical inference in population genomics, P Johri, CF Aquadro, M Beaumont, B Charlesworth… - PLoS …, 2022 - journals.plos.org
  • On the prospect of achieving accurate joint estimation of selection with population history, P Johri, A Eyre-Walker, RN Gutenkunst… - Genome biology and …, 2022 - academic.oup.com
  • Human genetic admixture through the lens of population genomics, S Gopalan, SP Smith, K Korunes… - … of the Royal …, 2022 - royalsocietypublishing.org
  • Consilience of methods for phylogenetic analysis of variance, DC Adams, ML Collyer - Evolution, 2022 - Wiley Online Library
  • Ethanol resistance in Drosophila melanogaster has increased in parallel cold‐adapted populations and shows a variable genetic architecture within and between …, QD Sprengelmeyer, JE Pool - Ecology and Evolution, 2021 - Wiley Online Library
  • Numerical simulation of the two-locus Wright-Fisher stochastic differential equation with application to approximating transition probability densities, Z He, M Beaumont, F Yu - bioRxiv, 2020 - biorxiv.org
  • Spatially explicit summary statistics for historical population genetic inference, DF Alvarado‐Serrano… - Methods in Ecology and …, 2016 - Wiley Online Library
  • Genetic Mapping by Bulk Segregant Analysis in Drosophila Experimental Design and Simulation-Based Inference, JE Pool - Genetics, 2016 - academic.oup.com
  • A Variable Genetic Architecture of Melanic Evolution in Drosophila melanogaster, H Bastide, JD Lange, JB Lack, A Yassin, JE Pool - Genetics, 2016 - academic.oup.com
  • Phylodynamic inference with kernel ABC and its application to HIV epidemiology, AFY Poon - Molecular biology and evolution, 2015 - academic.oup.com
  • Consequential Repetition Microsatellites as Targets of Natural Selection, RJ Haasl - 2013 - search.proquest.com
  • Bayesian identification of admixture events using multilocus molecular markers, J Corander, P Marttinen - Molecular ecology, 2006 - Wiley Online Library

    • Epidemiology

  • Using mechanistic model-based inference to understand and project epidemic dynamics with time-varying contact and vaccination rates, MJ Plank, SC Hendy, RN Binny, G Vattiato, A Lustig… - Scientific Reports, 2022 - nature.com
  • Hardware-accelerated Simulation-based Inference of Stochastic Epidemiology Models for COVID-19, S Kulkarni, MM Krell, S Nabarro, CA Moritz - ACM Journal on Emerging …, 2022 - dl.acm.org
  • Computational Modeling, Parameterization, and Evaluation of the Spread of Diseases, R Marin - 2022 - diva-portal.org
  • A hybrid stochastic model and its Bayesian identification for infectious disease screening in a university campus with application to massive COVID-19 screening at …, M Arnst, G Louppe, R Van Hulle, L Gillet… - Mathematical …, 2022 - Elsevier
  • Planning as Inference in Epidemiological Dynamics Models, F Wood, A Warrington, S Naderiparizi… - Frontiers in Artificial …, 2022 - frontiersin.org
  • Model selection and parameter estimation for dynamic epidemic models via iterated filtering application to rotavirus in Germany, T Stocks, T Britton, M Höhle - Biostatistics, 2020 - academic.oup.com
  • Calibration of individual-based models to epidemiological data A systematic review, CM Hazelbag, J Dushoff, EM Dominic… - PLoS computational …, 2020 - journals.plos.org
  • Quantifying transmission of emerging zoonoses using mathematical models to maximize the value of surveillance data, MR Ambrose, AJ Kucharski, P Formenty… - BioRxiv, 2019 - biorxiv.org
  • Stochastic dynamic modelling and statistical analysis of infectious disease spread and cancer treatment, T Stocks - 2018 - diva-portal.org
  • Approximate Bayesian computation and simulation-based inference for complex stochastic epidemic models, TJ McKinley, I Vernon, I Andrianakis, N McCreesh… - 2018 - projecteuclid.org
  • Biostatistical Genetics and Genetic Epidemiology, ER Ziegel - 2002 - Taylor & Francis

    • Medicine

  • Probabilistic Inference on Virtual Brain Models of Disorders, M Hashemi, A ZIAEE-MEHR, M WOODMAN… - bioRxiv, 2024 - biorxiv.org
  • Amortized simulation-based frequentist inference for tractable and intractable likelihoods, A Al Kadhim, H Prosper, O Prosper - Machine Learning: Science …, 2024 - iopscience.iop.org
  • Impacts of Digitalization on Content and Goals of Statistics Education, R Biehler, D Frischemeier, R Gould… - Handbook of Digital …, 2023 - Springer
  • Wastewater-based epidemiological modeling for continuous surveillance of covid-19 outbreak, M Fazli, S Sklar, MD Porter, BA French… - … Conference on Big …, 2021 - ieeexplore.ieee.org
  • OutbreakFlow Model-based Bayesian inference of disease outbreak dynamics with invertible neural networks and its application to the COVID-19 pandemics …, ST Radev, F Graw, S Chen, NT Mutters… - PLoS computational …, 2021 - journals.plos.org
  • Simulation-free estimation of an individual-based SEIR model for evaluating nonpharmaceutical interventions with an application to COVID-19 in the District of …, DK Sewell, A Miller, CDC MInD-Healthcare Program - PloS one, 2020 - journals.plos.org
  • On the identifiability of transmission dynamic models for infectious diseases, J Lintusaari, MU Gutmann, S Kaski, J Corander - Genetics, 2016 - academic.oup.com
  • Simulation-based models of emergency departments Operational, tactical, and strategic staffing, S Zeltyn, YN Marmor, A Mandelbaum… - ACM Transactions on …, 2011 - dl.acm.org
  • Toward simulation-based real-time decision-support systems for emergency departments, YN Marmor, S Wasserkrug, S Zeltyn… - Proceedings of the …, 2009 - ieeexplore.ieee.org
  • Ecological and immunological determinants of dengue epidemics, HJ Wearing, P Rohani - Proceedings of the National …, 2006 - National Acad Sciences
  • Modeling in Medical Decision Making, ER Ziegel - 2002 - Taylor & Francis

    • Geography

  • Analytical and Stochastic Numerical Methods for the Simulation of Subsurface Flow in Floodplains, JT Allgeier - 2023 - tobias-lib.ub.uni-tuebingen.de
  • Towards calibration of physics-based integrated surface-groundwater models using deep-learning based surrogates and simulation based inference, A Bennett, B Horowitz, E Leonarduzzi… - AGU Fall Meeting …, 2022 - ui.adsabs.harvard.edu
  • Parameter inference and uncertainty quantification for an intermediate complexity climate model, B Roeder, J Schloer… - EGU General Assembly …, 2022 - ui.adsabs.harvard.edu
  • A Deep Learning Emulator for a Groundwater Model Mapping Steady-State Water Table Depth, A Paulraj, A Bennett, Y Ma, L Condon… - AGU Fall Meeting …, 2022 - ui.adsabs.harvard.edu
  • Machine learning for weather and climate are worlds apart, D Watson-Parris - … Transactions of the Royal Society A, 2021 - royalsocietypublishing.org
  • Case studies of predictive uncertainty quantification for geothermal models, J Omagbon, J Doherty, A Yeh, R Colina, J O'Sullivan… - Geothermics, 2021 - Elsevier
  • Comparing spatial patterns, J Long, C Robertson - Geography Compass, 2018 - Wiley Online Library
  • Simulation based inference methods in a climate forced dynamical model of P. falciparum transmission in Colombia, T Stocks, S Bernal-García… - … on Mathematical Models …, 2017 - researchgate.net

    • Social Science

  • 3.10 Simulation Based Analysis of Social Systems–Models, Data and Policy, M Lees - Computer Science Methods for Effective and …, 2023 - drops.dagstuhl.de
  • Likelihood-free Bayesian inference for dynamic, stochastic simulators in the social sciences, J Dyer - 2022 - ora.ox.ac.uk
  • Granting forgiveness State and trait evidence for genetic and gender indirect effects through empathy, C vanOyen Witvliet, LM Root Luna… - The Journal of …, 2020 - Taylor & Francis
  • Global network inference from ego network samples testing a simulation approach, JA Smith - The Journal of Mathematical Sociology, 2015 - Taylor & Francis
  • Direct social perception and dual process theories of mindreading, M Herschbach - Consciousness and Cognition, 2015 - Elsevier
  • How Bayesian analysis cracked the red-state, blue-state problem, A Gelman - Statistical science, 2014 - JSTOR
  • Treatment of non-response in longitudinal network studies, M Huisman, C Steglich - Social networks, 2008 - Elsevier

    • Ecology

  • Easy, fast and reproducible Stochastic Cellular Automata with'chouca', A Genin, G Dupont, D Valencia, M Zucconi… - bioRxiv, 2023 - biorxiv.org
  • A unified model of species abundance, genetic diversity, and functional diversity reveals the mechanisms structuring ecological communities, I Overcast, M Ruffley, J Rosindell… - Molecular Ecology …, 2021 - Wiley Online Library
  • ecolottery Simulating and assessing community assembly with environmental filtering and neutral dynamics in R, F Munoz, M Grenié, P Denelle… - Methods in Ecology …, 2018 - Wiley Online Library
  • An overview of the utility of population simulation software in molecular ecology, S Hoban - Molecular ecology, 2014 - Wiley Online Library
  • Source–sink dynamics structure a common montane mammal, KIM O'KEEFE, UMA Ramakrishnan… - Molecular …, 2009 - Wiley Online Library
  • Seascape genetics and the spatial ecology of marine populations, KA Selkoe, CM Henzler, SD Gaines - Fish and fisheries, 2008 - Wiley Online Library

    • Evolutionary biology

  • PhyloCoalSimulations A simulator for network multispecies coalescent models, including a new extension for the inheritance of gene flow, J Fogg, ES Allman, C Ané - bioRxiv, 2023 - biorxiv.org
  • Mutation rate, selection, and epistasis inferred from RNA virus haplotypes via neural posterior estimation, I Caspi, M Meir, N Ben Nun, A Stern, Y Ram - bioRxiv, 2023 - biorxiv.org
  • Inference of population genetics parameters using discriminator neural networks an adversarial Monte Carlo approach, G Gower, P Iáñez Picazo, F Lindgren, F Racimo - bioRxiv, 2023 - biorxiv.org
  • Deep Learning from Phylogenies for Diversification Analyses, S Lambert, J Voznica, H Morlon - bioRxiv, 2022 - biorxiv.org
  • Simulation-based inference of evolutionary parameters from adaptation dynamics using neural networks, G Avecilla, JN Chuong, F Li, G Sherlock, D Gresham… - bioRxiv, 2021 - biorxiv.org
  • PipeMaster inferring population divergence and demographic history with approximate Bayesian computation and supervised machine-learning in R, M Gehara, GG Mazzochinni, F Burbrink - BioRxiv, 2020 - biorxiv.org

    • Environmental Science

  • A field-level emulator for modeling baryonic effects across hydrodynamic simulations, D Sharma, B Dai, F Villaescusa-Navarro… - arXiv preprint arXiv …, 2024 - arxiv.org
  • Uncertainty quantification for melt rate parameters in ice shelves using simulation-based inference, G Moss, V Višnjević, C Schröder… - EGU General …, 2022 - ui.adsabs.harvard.edu
  • Simulation based inference on stochastic volatility models in an environmental study, E Amiri - 2010 International Conference on Environmental …, 2010 - ieeexplore.ieee.org
  • Encyclopedia of Environmetrics Vols. 1-4, ER Ziegel - 2002 - Taylor & Francis

    • Cognitive Science

  • Mental speed is high until age 60 as revealed by analysis of over a million participants, M von Krause, ST Radev, A Voss - Nature human behaviour, 2022 - nature.com
  • Flexible and efficient simulation-based inference for models of decision-making, J Boelts, JM Lueckmann, R Gao, JH Macke - Elife, 2022 - elifesciences.org
  • Likelihood approximation networks (LANs) for fast inference of simulation models in cognitive neuroscience, A Fengler, LN Govindarajan, T Chen, MJ Frank - Elife, 2021 - elifesciences.org
  • EMBODIED CONSTRUCTION GRAMMAR APPROACH TO COMPOSITIONALITY AND CONCEPTUAL REPRESENTATION, CMB Callejas - 2004 - Citeseer

    • Robotics

  • DiSECt a differentiable simulator for parameter inference and control in robotic cutting, E Heiden, M Macklin, Y Narang, D Fox, A Garg… - Autonomous …, 2023 - Springer
  • Bayesian Object Models for Robotic Interaction with Differentiable Probabilistic Programming, KM Jatavallabhula, M Macklin, D Fox… - … on Robot Learning, 2023 - proceedings.mlr.press
  • Robot learning from randomized simulations A review, F Muratore, F Ramos, G Turk, W Yu… - Frontiers in Robotics …, 2022 - frontiersin.org
  • Sim2Real in robotics and automation Applications and challenges, S Höfer, K Bekris, A Handa, JC Gamboa… - IEEE transactions on …, 2021 - ieeexplore.ieee.org

    • Systems biology

  • Model-based inference of a plant-specific dual role for HOPS in regulating guard cell vacuole fusion, C Hodgens, D Flaherty, AM Pullen, I Khan, NJ English… - bioRxiv, 2023 - biorxiv.org
  • Missing data in amortized simulation-based neural posterior estimation, Z Wang, J Hasenauer, Y Schaelte - bioRxiv, 2023 - biorxiv.org
  • FitMultiCell Simulating and parameterizing computational models of multi-scale and multi-cellular processes, E Alamoudi, Y Schälte, R Müller, J Starruss… - bioRxiv, 2023 - biorxiv.org
  • A profile likelihood-based workflow for identifiability analysis, estimation, and prediction with mechanistic mathematical models, MJ Simpson, OJ Maclaren - bioRxiv, 2022 - biorxiv.org

    • Electrical Engineering and Systems Science

  • $μ$GUIDE a framework for microstructure imaging via generalized uncertainty-driven inference using deep learning, M Jallais, M Palombo - arXiv preprint arXiv:2312.17293, 2023 - arxiv.org
  • Energy-efficient network activity from disparate circuit parameters, M Deistler, JH Macke… - Proceedings of the …, 2022 - National Acad Sciences
  • Estimation of switching activity in sequential circuits using dynamic bayesian networks, S Bhanja, K Lingasubramanian… - … Conference on VLSI …, 2005 - ieeexplore.ieee.org

    • Bioinformatics

  • Modelling capture efficiency of single cell RNA-sequencing data improves inference of transcriptome-wide burst kinetics, W Tang, ACS Jørgensen, S Marguerat, P Thomas… - bioRxiv, 2023 - biorxiv.org
  • Efficient inference for agent-based models of real-world phenomena, ACS Jørgensen, A Ghosh, M Sturrock, V Shahrezaei - bioRxiv, 2021 - biorxiv.org
  • Cytopath Simulation based inference of differentiation trajectories from RNA velocity fields, R Gupta, D Cerletti, G Gut, A Oxenius, M Claassen - bioRxiv, 2020 - biorxiv.org

    • Biophysics

  • Rapid coarse-grained simulation of whole cryo-tomograms, C Purnell, J Heebner, MT Swulius - Biophysical journal, 2023 - cell.com
  • Quantifying binding kinetics with fluorescence microscopy, S Bryan IV, S Pressé, DP Herten, S Tashev… - Biophysical journal, 2023 - cell.com
  • A maximum mean discrepancy approach reveals subtle changes in α-synuclein dynamics, H Verdier, F Laurent, A Cassé, CL Vestergaard… - bioRxiv, 2022 - biorxiv.org

    • Mathematical

  • Approximate Bayesian parameterization of a complex tropical forest model, F Hartig, C Dislich, T Wiegand, A Huth - Biogeosciences Discussions, 2013 - Citeseer

    • Geology

  • Towards assembling the internal ice stratigraphy in coastal regions of Dronning Maud Land, East Antarctica, R Drews, I Koch, F Oraschewski… - EGU General …, 2022 - ui.adsabs.harvard.edu

    • Musicology

  • Examining Back-to-Back plays by gender, race, & sexual orientation, Jan Diehm, Jada Watson - The Pudding, 2023 - pudding.cool

    • statistical inference

  • Bayesian model calibration for wetting processes via simulation-based inference and measure transport, H Bonart, Y Marzouk, S Hardt - Bulletin of the American Physical Society, 2023 - APS

    • Chemistry

  • Simulation-based inference for stochastic gravitational wave background data analysis, J Alvey, U Bhardwaj, V Domcke, M Pieroni… - arXiv preprint arXiv …, 2023 - arxiv.org

    • Uncategorized

  • Constraining Protoplanetary Disk Winds from Forbidden Line Profiles with Simulation-based Inference, A Nemer, CH Hahn, J Li, P Melchior… - The Astrophysical …, 2024 - iopscience.iop.org
  • Modeling Digital Twins of Kubernetes-Based Applications, D Borsatti, W Cerroni, L Foschini… - … IEEE Symposium on …, 2023 - ieeexplore.ieee.org
  • Stochastic Gradient Bayesian Optimal Experimental Designs for Simulation-based Inference, VD Zaballa, EE Hui - ArXiv, 2023 - ncbi.nlm.nih.gov
  • sbi Simulation-based inference toolkit, A Tejero-Cantero, J Boelts, M Deistler… - Astrophysics …, 2023 - ui.adsabs.harvard.edu
  • Simulation-based inference and its applications in neuroscience, G Louppe - Networks of Spiking Neurons, 2023 - orbi.uliege.be