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TuringLang /Turing.jl

Bayesian inference with probabilistic programming.

machine-learning julia-language artificial-intelligence probabilistic-programming bayesian-inference mcmc turing hacktoberfest probabilistic-graphical-models hmc hamiltonian-monte-carlo bayesian-statistics probabilistic-models bayesian-neural-networks probabilistic-inference

UpdatedMay 7, 2025
Julia

blackjax-devs /blackjax

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

probabilistic-programming bayesian-inference hamiltonian-monte-carlo sampling-methods

UpdatedApr 27, 2025
Python

TuringLang /AdvancedHMC.jl

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

mcmc hacktoberfest hmc hamiltonian-monte-carlo nuts

UpdatedMay 7, 2025
Jupyter Notebook

tpapp /DynamicHMC.jl

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

julia julia-language bayesian-methods bayesian bayesian-inference hamiltonian-monte-carlo bayesian-statistics hybrid-monte-carlo

UpdatedMay 7, 2025
Julia

mici

matt-graham /mici

Manifold Markov chain Monte Carlo methods in Python

python mcmc hmc hamiltonian-monte-carlo markov-chain-monte-carlo hybrid-monte-carlo inference-algorithms

UpdatedApr 24, 2025
Python

kthohr /mcmc

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

cpp automatic-differentiation eigen cpp11 armadillo differential-evolution mcmc hmc hamiltonian-monte-carlo markov-chain-monte-carlo de metropolis-hastings eigen3 mala langevin-diffusion riemannian-manifold

UpdatedFeb 8, 2024
C++

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

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

finance trading investing project-management probabilistic-programming monte-carlo-simulation uncertainty-quantification hamiltonian-monte-carlo markov-chain-monte-carlo portfolio-theory epistemology probabilistic-models maximum-likelihood-estimation capm ensemble-machine-learning aleatoric-uncertainty epistemic-uncertainty ontological-information generative-ai npv-analysis

UpdatedApr 19, 2025
Jupyter Notebook

m-clark /bayesian-basics

🚫 ↩️ A document that introduces Bayesian data analysis.

r bayesian-methods rstan bayesian bayesian-inference stan brms rstanarm mcmc regression-models likelihood bayesian-data-analysis hamiltonian-monte-carlo bayesian-statistics bayesian-analysis posterior-probability metropolis-hastings gibbs prior posterior-predictive

UpdatedFeb 21, 2022
Stan

saforem2 /l2hmc-qcd

Application of the L2HMC algorithm to simulations in lattice QCD.

machine-learning deep-learning tensorflow monte-carlo pytorch hydra lattice mcmc hmc hamiltonian-monte-carlo lattice-qcd horovod gauge-theory deepspeed

UpdatedFeb 2, 2024
Jupyter Notebook

models-by-example

m-clark /models-by-example

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

machine-learning neural-network algorithms linear-regression lasso pca expectation-maximization splines logistic-regression bayesian gradient-descent rkhs ridge-regression gaussian-processes cox-model hamiltonian-monte-carlo mixed-models penalized-regression maximum-likelihood-estimation zero-inflated

UpdatedJan 28, 2021
R

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

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

python data-science clustering-algorithm kmeans-clustering hamiltonian-monte-carlo gibbs-sampling maximum-likelihood-estimation monte-carlo-sampling mathematica-notebook

UpdatedSep 19, 2017
Jupyter Notebook

lxuechen /BDMC

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

pytorch bayesian-inference mcmc hamiltonian-monte-carlo annealed-importance-sampling bidirectional-monte-carlo

UpdatedMay 14, 2021
Python

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.

uncertainty survival-analysis rstan health-economic-evaluation inla hamiltonian-monte-carlo survival-models frequentist plotting-survival-curves

UpdatedApr 14, 2025
R

larsgeb /hmclab

inversion geophysics bayesian-inference tomography hamiltonian-monte-carlo markov-chain-monte-carlo

UpdatedSep 22, 2023
Jupyter Notebook

Generalised-Gaussian-Processes

vr308 /Generalised-Gaussian-Processes

Fully Bayesian Inference in GPs - Gaussian and Generic Likelihoods

inference gaussianprocess mcmc variational-inference hamiltonian-monte-carlo marginalisation

UpdatedSep 26, 2023
Python

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).

neural-networks bayesian-inference hamiltonian-monte-carlo sampling-methods langevin-dynamics no-u-turn-sampler physics-informed-neural-networks

UpdatedJan 14, 2023
Python

ipeis /HH-VAEM

Official code for HH-VAEM

deep-learning pytorch vae missing-data hamiltonian-monte-carlo pytorch-lightning

UpdatedJan 28, 2023
Python

aripakman /hmc-binary

Exact Hamiltonian Monte Carlo Sampler for Binary Distributions

monte-carlo matlab hamiltonian-monte-carlo

UpdatedOct 14, 2015
C++

JohannesBuchner /PinNUTS

PinNUTS🥜 is dynamic Hamiltonian Monte Carlo algorithm implemented in Python

monte-carlo pure-python mcmc hamiltonian-monte-carlo no-u-turn-sampler

UpdatedFeb 7, 2020
Python

aripakman /hmc-tmg

Exact Hamiltonian Monte Carlo Sampler for Truncated Multivariate Gaussians

monte-carlo mcmc hamiltonian-monte-carlo

UpdatedFeb 11, 2020
MATLAB

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