Popular GitHub Repositories for Hamiltonian Monte Carlo

Fully Bayesian Inference in GPs - Gaussian and Generic Likelihoods

The code enables to perform Bayesian inference in an efficient manner through the use of Hamiltonian Neural Networks (HNNs), Deep Neural Networks (DNNs), Neural ODEs, and Symplectic Neural Networks (SympNets) used with state-of-the-art sampling schemes like Hamiltonian Monte Carlo (HMC) and the No-U-Turn-Sampler (NUTS).

Official code for HH-VAEM

An experimental Python package for learning Bayesian Neural Network.

Hamiltonian Annealed Importance Sampling (HAIS) in tensorflow

Bayesian Neural Networks implemented in Julia using variational inference and Hamiltonian Monte Carlo sampling.