Software

An initial list of SBI-related software packages

SBI (python) - general purpose SBI framework
SBI Benchmarking (python) - for benchmarking
MadMiner - aimed at particle physics
swyft (python) the reference implementation of Truncated Marginal Neural Ratio Estimation (TMNRE), an efficient, simulation-based inference technique for complex data and expensive simulators
carl an early NN-based SBI package
lampe (python) is a flexible, amortized sbi library. The philosophy of LAMPE is to avoid obfuscation and expose all components so it is most useful for researchers.
pydelfi (python) with neural density estimators and adaptive acquisition of simulations.

Latest Posts

Fast, Accurate and Perturbative Forward Modeling of Galaxy Clustering Part I Galaxies in the Restframe

J Stadler, F Schmidt, M Reinecke - arXiv preprint arXiv:2409.10937, 2024 - arxiv.org

… Forward models of the galaxy density field enable simulation based inference as well as field level inference of galaxy clustering. However, these analysis techniques …

The cosmological analysis of X-ray cluster surveys VI. Inference based on analytically simulated observable diagrams

M Kosiba, N Cerardi, M Pierre, F Lanusse… - arXiv preprint arXiv …, 2024 - arxiv.org

… In this paper, we use a simulation-based inference method utilizing artificial neural networks to optimally extract cosmological information from a shallow X-ray survey, …

Cell-mechanical parameter estimation from 1D cell trajectories using simulation-based inference

J Heyn, M Atienza Juanatey, M Falcke, J Raedler - bioRxiv, 2024 - biorxiv.org

… employ simulation-based inference (SBI) to estimate cell specific model parameters from … In this paper we studied the application of simulation-based inference (SBI ) to …

Ensemble surrogate modeling of advective-dispersive transport with intraparticle diffusion model for column-leaching test

A Ershadi, M Finkel, B Liu, OA Cirpka… - Journal of Contaminant …, 2024 - Elsevier

… We applied our proposed ensemble surrogate model to estimate the complete posterior parameter distribution using Simulation-Based Inference, specifically Neural …