Bayesian Modeling and Probabilistic Programming in Python

Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.

Bayesian inference with probabilistic programming.

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

The Python ensemble sampling toolkit for affine-invariant MCMC

• Updated Sep 23, 2025
• OCaml

RStan, the R interface to Stan

Bayesian Data Analysis demos for Python

Boltzmann Machines in TensorFlow with examples

Bitmap generation from a single example with convolutions and MCMC

Doing Bayesian Data Analysis, 2nd Edition (Kruschke, 2015): Python/PyMC3 code

Bayesian Data Analysis demos for R

bayesplot R package for plotting Bayesian models

DGMs for NLP. A roadmap.

Collection of Monte Carlo (MC) and Markov Chain Monte Carlo (MCMC) algorithms applied on simple examples.

Julia package with selected functions in the R package `rethinking`. Used in the SR2... projects.

High-performance Bayesian Data Analysis on the GPU in Clojure

Robust, modular and efficient implementation of advanced Hamiltonian Monte Carlo algorithms

A batteries-included toolkit for the GPU-accelerated OpenMM molecular simulation engine.

ParaMonte: Parallel Monte Carlo and Machine Learning Library for Python, MATLAB, Fortran, C++, C.