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

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

Bayesian inference with probabilistic programming.

PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks

tmLQCD is a freely available software suite providing a set of tools to be used in lattice QCD simulations. This is mainly a HMC implementation (including PHMC and RHMC) for Wilson, Wilson Clover and Wilson twisted mass fermions and inverter for different versions of the Dirac operator. The code is fully parallelised and ships with optimisations…

A C++ library of Markov Chain Monte Carlo (MCMC) methods

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

Manifold Markov chain Monte Carlo methods in Python

A pure Python client library for the IBM Z HMC Web Services API

A native Julia code for lattice QCD with dynamical fermions in 4 dimension.

AeMCMC is a Python library that automates the construction of samplers for Aesara graphs representing statistical models.

A CLI for the IBM Z HMC

An Ansible collection for the IBM Z HMC

A Prometheus exporter for the IBM Z HMC

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

Application of the L2HMC algorithm to simulations in lattice QCD.

Bayesian Generalized Linear models using `@formula` syntax.

An HMC/NUTS implementation in Aesara

Phylogenetic inference using Stan

Hybrid Memory Cube Simulation & Research Infrastructure