286 Open source projects that are alternatives of or similar to Pymc3

A web interface for exploring PyMC3 traces

GPstuff - Gaussian process models for Bayesian analysis

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

Bayesian Coherent Point Drift (BCPD/BCPD++); Source Code Available

A collection of Methods and Models for various architectures of Artificial Neural Networks

Scalable inference for a generative model of astronomical images

A Bayesian Analysis Toolkit in Julia

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

Bayesian Evolutionary Analysis by Sampling Trees

CmdStanR: the R interface to CmdStan

Julia package for automatic Bayesian inference on a factor graph with reactive message passing

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

Modular Probabilistic Programming on MXNet

A Latent Dirichlet Allocation implementation in Python.

Bayesian Data Analysis demos for Python

Distributed Bayesian Entity Resolution in Apache Spark

Fast & scalable MCMC for all your exoplanet needs!

Statistical Rethinking (2nd Ed) with Tensorflow Probability

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)

Automatic Reparameterisation of Probabilistic Programs

Blang's software development kit

The Microbiome Interpretable Temporal Rule Engine

Regression with Summary Statistics.

Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)

Sequential Monte Carlo algorithm for approximation of posterior distributions.

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

DGMs for NLP. A roadmap.

Full Bayesian Inference for Hidden Markov Models

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

Deep universal probabilistic programming with Python and PyTorch

Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.

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

Nested Sampling post-processing and plotting

Boltzmann Machines in TensorFlow with examples

Material for a workshop on Bayesian stats with R

High-performance Bayesian Data Analysis on the GPU in Clojure

Bayesian inference with probabilistic programming.

RStan, the R interface to Stan

The base NIMBLE package for R

Bayesian Data Analysis demos for R

Efficient, lightweight variational inference and approximation bounds

Bayesian Deep Learning with Stochastic Gradient MCMC Methods

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

Single-cell copy number calling and event history reconstruction.

shinystan R package and ShinyStan GUI

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

Natural Gradient, Variational Inference

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

Sleek implementations of the ZigZag, Boomerang and other assorted piecewise deterministic Markov processes for Markov Chain Monte Carlo including Sticky PDMPs for variable selection

Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch

Jupyter notebooks with examples of statistical methods and analyses using R.

Lecture notes on Bayesian deep learning

Python package for point cloud registration using probabilistic model (Coherent Point Drift, GMMReg, SVR, GMMTree, FilterReg, Bayesian CPD)

Particle filtering and sequential parameter inference in Python

Forecasting 🇫🇷 elections with Bayesian statistics 🥳

rstanarm R package for Bayesian applied regression modeling

Ladder Variational Autoencoders (LVAE) in PyTorch

Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)

Jupyter Notebooks for Springer book "Python for Probability, Statistics, and Machine Learning"