140 Open Source Mcmc Software Projects

Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Aesara

The Python ensemble sampling toolkit for affine-invariant MCMC

Bayesian inference with probabilistic programming.

Owl - OCaml Scientific and Engineering Computing @ http://ocaml.xyz

Boltzmann Machines in TensorFlow with examples

Bayesian Data Analysis demos for Python

RStan, the R interface to Stan

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

Bitmap generation from a single example with convolutions and MCMC

Doing Bayesian Data Analysis, 2nd Edition (Kruschke, 2015): Python/PyMC3 code

Bayesian Data Analysis demos for R

High-performance Bayesian Data Analysis on the GPU in Clojure

bayesplot R package for plotting Bayesian models

Collection of probabilistic models and inference algorithms

Collection of Monte Carlo (MC) and Markov Chain Monte Carlo (MCMC) algorithms applied on simple examples.

shinystan R package and ShinyStan GUI

Stan.jl illustrates the usage of the 'single method' packages, e.g. StanSample, StanOptimize, etc.

Bayesian Evolutionary Analysis by Sampling Trees

DGMs for NLP. A roadmap.

Manifold Markov chain Monte Carlo methods in Python

Bayesian Evolutionary Analysis Sampling Trees

Fast & scalable MCMC for all your exoplanet needs!

GPstuff - Gaussian process models for Bayesian analysis

Graphical tools for analyzing Markov Chain Monte Carlo simulations from Bayesian inference

PhyML -- Phylogenetic estimation using (Maximum) Likelihood

The base NIMBLE package for R

Gathers Machine learning models using pure Numpy to cover feed-forward, RNN, CNN, clustering, MCMC, timeseries, tree-based, and so much more!

Types and utility functions for summarizing Markov chain Monte Carlo simulations

A batteries-included toolkit for the GPU-accelerated OpenMM molecular simulation engine.

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

MCMC sample analysis, kernel densities, plotting, and GUI

Implementation of Markov Chain Monte Carlo in Python from scratch

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

A repository to keep track of all the code that I end up writing for my blog posts.

A statistical toolbox for diffusion processes and stochastic differential equations. Named after the Brownian Bridge.

Implementing MCMC sampling from scratch in R for various Bayesian models

General-Purpose MCMC and SMC Samplers and Tools for Bayesian Statistics

Implementations of the models from the Statistical Rethinking book with Turing.jl

Use MCMC to analyze districting plans and gerrymanders

The posterior R package

A Bayesian Analysis Toolkit in Julia

Simulation, visualization, and inference tools for modelling the spread of infectious diseases with Julia

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

Tools for Flexible Spectroscopic Inference

Reproducing plots of Bayesian Data Analysis (Gelman et al, 3rd Edition) in Python

A web interface for exploring PyMC3 traces

VIP is a python package/library for angular, reference star and spectral differential imaging for exoplanet/disk detection through high-contrast imaging.

Bayesian Data Analysis demos for Matlab/Octave

Geophysical Bayesian Inference in Python. Docs:

Using neural network to build expressive hierarchical distribution; A variational method to accurately estimate posterior uncertainty; A fast and general method for Bayesian inference. (ICML 2018)

⚡️ zeus: Lightning Fast MCMC ⚡️

Python library for stochastic numerical optimization

Distributed Bayesian Entity Resolution in Apache Spark

Regression with Summary Statistics.

Simulated Method of Moments for Julia

Sequential Monte Carlo algorithm for approximation of posterior distributions.

The sample question for Interview a job in Binary options

Bayesian Statistics I at Stockholm University

Python implementation of MATLAB toolbox "mcmcstat"

CmdStanR: the R interface to CmdStan

Build dirichletprocess objects for data analysis

Examples for Bayesian inference using DynamicHMC.jl and related packages.

BAS R package https://merliseclyde.github.io/BAS/

AAAI & CVPR 2016: Preconditioned Stochastic Gradient Langevin Dynamics (pSGLD)

MCMC toolbox for Matlab

Full Bayesian Inference for Hidden Markov Models

Bayesian Generalized Linear Models with Time-Varying Coefficients

library of C++ functions that support applications of Stan in Pharmacometrics

machine learning

Python MCMC Sampler

Bayesian Deep Learning with Stochastic Gradient MCMC Methods

Automatic Reparameterisation of Probabilistic Programs

Nested Sampling post-processing and plotting

Documentation, models and code relating to the 3rd edition of the textbook Stochastic Modelling for Systems Biology

Multi-core BUGS for fast Bayesian inference of large hierarchical models

Markov chain Monte Carlo solver for lattice spin systems implemented by Julialang

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

A Bayesian latent tree model of high-dimensional heterogeneous data

NumCosmo main code

A multi-planet Radial Velocity and Transit modelling software

農研機構統計研修「ベイズ統計モデリングとMCMC」

Latent Dirichlet Allocation

dEploid is designed for deconvoluting mixed genomes with unknown proportions. Traditional ‘phasing’ programs are limited to diploid organisms. Our method modifies Li and Stephen’s algorithm with Markov chain Monte Carlo (MCMC) approaches, and builds a generic framework that allows haloptype searches in a multiple infection setting.

Blang's software development kit

Make a sweet giant triangle confusogram (GTC) plot

A common framework for implementing and using log densities for inference.

Bayesian methods in deep learning Summer School

DynamicHMC versions of StatisticalRethinking models

Start with the Chempy tutorial

A fully Bayesian implementation of sequential model-based optimization

Robust implementation for random-walk Metropolis-Hastings algorithms

CorBinian: A toolbox for modelling and simulating high-dimensional binary and count-data with correlations

Python tools for Bayesian data analysis

An R Package for Hierarchical Bayesian Analysis of North American Breeding Bird Survey Data

Монте Карло изчисления с Python

Affine Invariant Markov Chain Monte Carlo (MCMC) Ensemble sampler

Accelerate MCMC algorithm on GPU for Big Data Applications

Curated materials for different machine learning related summer schools

Generic goodness of fit tests for random plain old data

An R package for Multi-Label Prediction Using Gibbs Sampling (and Classifier Chains)