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

Scalable Kernel-Based Distances for Statistical Inference and Integration

M Naslidnyk - arXiv preprint arXiv:2602.21846, 2026 - arxiv.org

… In Chapter 3 we propose a theoretically sound, improved estimator for MMD in simulation-based inference. Then, in Chapter 4, we propose an MMD-based estimator for …

Preconditioned Robust Neural Posterior Estimation for Misspecified Simulators

RP Kelly, DT Frazier, DJ Warne… - arXiv preprint arXiv …, 2026 - arxiv.org

… Simulation-based inference (SBI) enables parameter estimation for complex stochastic models with intractable likelihoods when model simulation is feasible. Neural …

Inferring the population properties of galactic binaries from LISA's stochastic foreground

F De Santi, A Santini, A Toubiana, N Karnesis… - arXiv preprint arXiv …, 2026 - arxiv.org

… We present a simulation-based inference framework to measure the population properties of galactic binaries directly from the reconstructed foreground. Adopting an …

BPS2026–Bayesian inference on reaction-diffusion models

B Nainggolan, P Pessoa, S Pressé - Biophysical Journal, 2026 - cell.com

… spatiotemporally resolved population dynamics while only requiring minutes-long acquisition periods makes it an ideal testbed for evaluating simulation-based inference (…