208 Open source projects that are alternatives of or similar to Mcmc

The base NIMBLE package for R

Bayesian Data Analysis demos for Python

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

GPstuff - Gaussian process models for Bayesian analysis

Bayesian Evolutionary Analysis by Sampling Trees

Bayesian Data Analysis demos for R

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

Sequential Monte Carlo algorithm for approximation of posterior distributions.

Fast & scalable MCMC for all your exoplanet needs!

Material for a workshop on Bayesian stats with R

A web interface for exploring PyMC3 traces

Bayesian inference with probabilistic programming.

shinystan R package and ShinyStan GUI

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

Single-cell copy number calling and event history reconstruction.

Blang's software development kit

ParaMonte: Plain Powerful Parallel Monte Carlo and MCMC Library for Python, MATLAB, Fortran, C++, C.

Bayesian Deep Learning with Stochastic Gradient MCMC Methods

High-performance Bayesian Data Analysis on the GPU in Clojure

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

Nested Sampling post-processing and plotting

A Bayesian Analysis Toolkit in Julia

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

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

RStan, the R interface to Stan

Distributed Bayesian Entity Resolution in Apache Spark

Full Bayesian Inference for Hidden Markov Models

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

Collection of probabilistic models and inference algorithms

BOPP: Bayesian Optimization for Probabilistic Programs

Scalable inference for a generative model of astronomical images

Personal project to compare hierarchical linear regression in PyMC3 and PyStan, as presented at http://pydata.org/london2016/schedule/presentation/30/ video: https://www.youtube.com/watch?v=Jb9eklfbDyg

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

Machine learning, in numpy

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

This repository contains morden baysian statistics and deep learning based research articles , software for survival analysis

Fast and Easy Infinite Neural Networks in Python

A qualitative probabilistic programming language based on ranking theory

Implementation of Bayesian Recurrent Neural Networks by Fortunato et. al

A probabilistic programming library for Bayesian deep learning, generative models, based on Tensorflow

Sequential Monte Carlo in python

Bayes by Backprop implemented in a CNN in PyTorch

Turing version of StatisticalRethinking models.

MrBayes is a program for Bayesian inference and model choice across a wide range of phylogenetic and evolutionary models. For documentation and downloading the program, please see the home page:

This project has moved to https://git.dynare.org/Dynare/dynare

Infer.NET is a framework for running Bayesian inference in graphical models

Simulation-based inference in PyTorch

Generalized linear mixed-effect model in Python

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

An extensible C++ library of Hierarchical Bayesian clustering algorithms, such as Bayesian Gaussian mixture models, variational Dirichlet processes, Gaussian latent Dirichlet allocation and more.

Modular Probabilistic Programming on MXNet

A Python package for building Bayesian models with TensorFlow or PyTorch

Dynamic Nested Sampling package for computing Bayesian posteriors and evidences

DGMs for NLP. A roadmap.

Manifold Markov chain Monte Carlo methods in Python

A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation

PyMC3 codes of Lee and Wagenmakers' Bayesian Cognitive Modeling - A Pratical Course

Example PyMC3 project for performing Bayesian data analysis using a probabilistic programming approach to machine learning.

Variational Bayesian Monte Carlo (VBMC) algorithm for posterior and model inference in MATLAB

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