Gaussian processes in TensorFlow

Machine learning algorithms for many-body quantum systems

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

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

Manifold Markov chain Monte Carlo methods in Python

A lightweight and performant implementation of HMC and NUTS in Python, spun out of the PyMC project.

Generalised Bayesian inversion framework

Code that implements Factor Analysis of Information Risk (FAIR) in combination with MITRE ATT&CK using Markov Chain Monte Carlo (via PyMC) to determine the frequency of successful attacks.

Bayesian Deep Learning with Stochastic Gradient MCMC Methods

Exploration of metropolis-hastings (local) and Uli Wolff (cluster) algorithms on the Ising Model

Markov Chain Monte Carlo MCMC methods are implemented in various languages (including R, Python, Julia, Matlab)

A straightforward Bayesian data fitting library

This repo contains the code of Transitional Markov chain Monte Carlo algorithm

A toolbox for inference of mixture models

Lightweight Bayesian deep learning library for fast prototyping based on PyTorch

BISIP | Bayesian inversion of spectral induced polarization laboratory data

Accelerating Monte Carlo methods for Bayesian inference in dynamical models

Code for 'Unbiased Monte Carlo Cluster Updates with Autoregressive Neural Networks'.

Classical models implemented from a Markov operator's perspective

Discrete Array Variable Reversible jump MCMC