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

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

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

Manifold Markov chain Monte Carlo methods in Python

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

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

Bayesian Generalized Linear models using `@formula` syntax.

Application of the L2HMC algorithm to simulations in lattice QCD.

A primer on Bayesian Neural Networks. The aim of this reading list is to facilitate the entry of new researchers into the field of Bayesian Deep Learning, by providing an overview of key papers. More details: "A Primer on Bayesian Neural Networks: Review and Debates"

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

Lightweight MCMC sampling for PyTorch Models aka My Corona Project

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

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 for various modern architectures, such as commodity PC clusters and the Blue Gene family.

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

Within-orbit Adaptive Leapfrog No-U-Turn Sampler

An HMC/NUTS implementation in Aesara

Phylogenetic inference using Stan

zOS Base Control Program internal interface

A Prometheus exporter for the IBM Z HMC

Hybrid Memory Cube Simulation & Research Infrastructure

Utilities of gauge fields

An Ansible collection for the IBM Z HMC

A Shiny app to help people learn (and play with) Hamiltonian Monte Carlo sampling

A CLI for the IBM Z HMC

Code accompanying the paper 'Manifold MCMC methods for Bayesian inference in a wide class of diffusion models'

HMCi is a utility that collects metrics from one or more IBM Power Hardware Management Consoles (HMC), without the need to install agents on logical partitions / virtual machines running on the IBM Power systems.

Bayesian deep learning experiments

Inference in differentiable generative models