A Python library for amortized Bayesian workflows using generative neural networks.

ELFI - Engine for Likelihood-Free Inference

R package for statistical inference using partially observed Markov processes

Density estimation likelihood-free inference. No longer actively developed see https://github.com/mackelab/sbi instead

A Python toolkit for (simulation-based) inference and the mechanization of science.

Inverse binomial sampling for efficient log-likelihood estimation of simulator models in MATLAB

Julia package for neural estimation

Approximate Bayesian Computation (ABC) with differential evolution (de) moves and model evidence (Z) estimates.

A Python implementation of EP-ABC for likelihood-free, probabilistic inference.

Likelihood-Free Inference for Julia.

Inverse binomial sampling for efficient log-likelihood estimation of simulator models in Python

Mining gold from implicit models to improve likelihood-free inference, example for ROLR and RASCAL.

Code for the paper "Sequential Bayesian Experimental Design for Implicit Models via Mutual Information", Bayesian Analysis 2021, https://arxiv.org/abs/2003.09379.

Inverse binomial sampling for efficient log-likelihood estimation of simulator models (old location)