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

PolySwyft sequential simulation-based nested sampling

KH Scheutwinkel, W Handley, C Weniger… - arXiv preprint arXiv …, 2025 - arxiv.org

… Abstract We present PolySwyft, a novel, non-amortised simulation-based inference framework that unites the strengths of nested sampling (NS) and neural ratio estimation …

Vision Transformers for Cosmological Fields Application to Weak Lensing Mass Maps

J Kakadia, S Agrawal, K Zhong, B Jain - arXiv preprint arXiv:2512.07125, 2025 - arxiv.org

… In Section 2, we introduce simulation-based inference, how vision models can be used to constrain cosmology from the field level, the simulations we use, and how we …

Neural Bayes estimation and selection of complex bivariate extremal dependence models

LM André, JL Wadsworth, R Huser - Extremes, 2025 - Springer

Likelihood-free approaches are appealing for performing inference on complex dependence models, either because it is not possible to formulate a likelihood function, or …

Network inference via approximate Bayesian computation. Illustration on a stochastic multipopulation neural mass model

S Ditlevsen, M Tamborrino… - The Annals of Applied …, 2025 - projecteuclid.org

This supplementary material contains three sections. In Section 1, we detail the derivation of the numerical splitting method, which is summarized in Algorithm 2 and used …