hamiltonian-monte-carlo

blackjax-devs/blackjax

BlackJAX is a Bayesian Inference library designed for ease of use, speed and modularity.

TuringLang/AdvancedHMC.jl

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

tpapp/DynamicHMC.jl

Implementation of robust dynamic Hamiltonian Monte Carlo methods (NUTS) in Julia.

matt-graham/mici

Manifold Markov chain Monte Carlo methods in Python

kthohr/mcmc

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

m-clark/bayesian-basics

:no_entry_sign: :leftwards_arrow_with_hook: A document that introduces Bayesian data analysis.

dkanungo/Probabilistic-ML-for-finance-and-investing

Probabilistic Machine Learning for Finance and Investing: A Primer to Generative AI with Python

m-clark/models-by-example

By-hand code for models and algorithms. An update to the 'Miscellaneous-R-Code' repo.

saforem2/l2hmc-qcd

Application of the L2HMC algorithm to simulations in lattice QCD.

physhik/Study-of-David-Mackay-s-book-

David Mackay's book review and problem solvings and own python codes, mathematica files

lxuechen/BDMC

PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.

giabaio/survHE

Survival analysis in health economic evaluation Contains a suite of functions to systematise the workflow involving survival analysis in health economic evaluation. survHE can fit a large range of survival models using both a frequentist approach (by calling the R package flexsurv) and a Bayesian perspective.

larsgeb/hmclab

vr308/Generalised-Gaussian-Processes

Fully Bayesian Inference in GPs - Gaussian and Generic Likelihoods

IdahoLabResearch/BIhNNs

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).

aripakman/hmc-binary

Exact Hamiltonian Monte Carlo Sampler for Binary Distributions

JohannesBuchner/PinNUTS

PinNUTS🥜 is dynamic Hamiltonian Monte Carlo algorithm implemented in Python

aripakman/hmc-tmg

Exact Hamiltonian Monte Carlo Sampler for Truncated Multivariate Gaussians

ipeis/HH-VAEM

Official code for HH-VAEM

armanbilge/phyloHMC

Hamiltonian Monte Carlo on the space of phylogenies

jandraor/SDR_Bayes

System Dynamics Review (2021)

CoastEgo/BinaryJax

Implementation of automatic differentiation in VBozza's BinaryLensing

compops/barx-sysid2018

Sparse Bayesian ARX models with flexible noise distributions

gil2rok/drghmc

Sampling From Multiscale Densities With Delayed Rejection Generalized Hamiltonian Monte Carlo.

ronaldseoh/ronald_bdl

An experimental Python package for learning Bayesian Neural Network.

flipdazed/Hybrid-Monte-Carlo

Used in Deep Machine Learning and Lattice Quantum Chromodynamics

giabaio/survHEhmc

Survival analysis in health economic evaluation using Bayesian modelling and Hamiltonian Monte Carlo Contains a suite of functions to systematise the workflow involving survival analysis in health economic evaluation.

JohnReid/HAIS

Hamiltonian Annealed Importance Sampling (HAIS) in tensorflow

draktr/monte-library

Monte is a set of Monte Carlo methods in Python. The package is written to be flexible, clear to understand and encompass variety of Monte Carlo methods.

gldmt-duke/CokerAmitaiSGHMC

An implementation of Stochastic Gradient Hamiltonian Monte Carlo by Gilad Amitai and Beau Coker

afiliot/Bayesian-Personalization-Of-A-Tumor-Growth-Model

Project on Medical Imaging - MVA MSc

ipeis/HMCTuning

Code for automatic HMC hyperparameter tuning

larsgeb/hmc-linear-systems

Hamiltonian Monte Carlo implemented for simple linear systems

MauroCE/IntegratorSnippets

Code implementing Integrator Snippets, joint work with Christophe Andrieu and Chang Zhang

andrejobuljen/JaxPM-Hi-Fi-mocks

JAX-powered Hi-Fi mocks