203 Open Source Bayesian Inference Software Projects
Free and open source bayesian inference code projects including engines, APIs, generators, and tools.
Pymc3 5310 ⭐
Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano
Zhusuan 1929 ⭐
A probabilistic programming library for Bayesian deep learning, generative models, based on Tensorflow
Stan Dev Stan 1927 ⭐
Stan development repository. The master branch contains the current release. The develop branch contains the latest stable development. See the Developer Process Wiki for details.
Causalnex 813 ⭐
A Python library that helps data scientists to infer causation rather than observing correlation.
Brms 768 ⭐
brms R package for Bayesian generalized multivariate non-linear multilevel models using Stan
Bayesian Neural Networks 745 ⭐
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
Numpyro 753 ⭐
Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.
Pytorch Bayesiancnn 689 ⭐
Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.
Dsge.jl 592 ⭐
Solve and estimate Dynamic Stochastic General Equilibrium models (including the New York Fed DSGE)
Bayesian Stats Modelling Tutorial 422 ⭐
How to do Bayesian statistical modelling using numpy and PyMC3
Statistical_rethinking_with_brms_ggplot2_and_the_tidyverse 346 ⭐
The bookdown version lives here: https://bookdown.org/content/3890
Pyvarinf 310 ⭐
Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch
Master Thesis Bayesiancnn 213 ⭐
Master Thesis on Bayesian Convolutional Neural Network using Variational Inference
Wiseodd Mcmc 198 ⭐
Collection of Monte Carlo (MC) and Markov Chain Monte Carlo (MCMC) algorithms applied on simple examples.
Dynamichmc.jl 155 ⭐
Implementation of robust dynamic Hamiltonian Monte Carlo methods (NUTS) in Julia.
Survival Analysis Using Deep Learning 130 ⭐
This repository contains morden baysian statistics and deep learning based research articles , software for survival analysis
Aboleth 126 ⭐
A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation
Dsteinberg Libcluster 126 ⭐
An extensible C++ library of Hierarchical Bayesian clustering algorithms, such as Bayesian Gaussian mixture models, variational Dirichlet processes, Gaussian latent Dirichlet allocation and more.
Mrbayes 115 ⭐
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:
Pymc3_vs_pystan 110 ⭐
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
Vbmc 105 ⭐
Variational Bayesian Monte Carlo (VBMC) algorithm for posterior and model inference in MATLAB
Translationalneuromodeling Tapas 107 ⭐
TAPAS - Translational Algorithms for Psychiatry-Advancing Science
Bayesian Cognitive Modeling In Pymc3 93 ⭐
PyMC3 codes of Lee and Wagenmakers' Bayesian Cognitive Modeling - A Pratical Course
Pymc Example Project 90 ⭐
Example PyMC3 project for performing Bayesian data analysis using a probabilistic programming approach to machine learning.
Alice 79 ⭐
NIPS 2017: ALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching
Bayesloop 82 ⭐
Probabilistic programming framework that facilitates objective model selection for time-varying parameter models.
Bijectors.jl 80 ⭐
Implementation of normalising flows and constrained random variable transformations
Bridge.jl 65 ⭐
A statistical toolbox for diffusion processes and stochastic differential equations. Named after the Brownian Bridge.
Books Making You Better 68 ⭐
A list of classic books make better you understand not only how it works, but why it works.
Autoencoders_keras 59 ⭐
Automatic feature engineering using deep learning and Bayesian inference using TensorFlow.
Nestle 61 ⭐
Pure Python, MIT-licensed implementation of nested sampling algorithms for evaluating Bayesian evidence.
Fbnn 55 ⭐
Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
Bayesian Basics 48 ⭐
:no_entry_sign: :leftwards_arrow_with_hook: A document that introduces Bayesian data analysis.
Variational_dropout 39 ⭐
Implementation of "Variational Dropout and the Local Reparameterization Trick" paper with Pytorch
Artificial_neural_networks 35 ⭐
A collection of Methods and Models for various architectures of Artificial Neural Networks
Hmm_for_autonomous_driving 33 ⭐
🎓 Educational application of Hidden Markov Model to Autonomous Driving 🚕🚙🚗
Dynamichmcexamples.jl 28 ⭐
Examples for Bayesian inference using DynamicHMC.jl and related packages.
Probqa 30 ⭐
Probabilistic question-asking system: the program asks, the users answer. The minimal goal of the program is to identify what the user needs (a target), even if the user is not aware of the existence of such thing/product/service. The maximal goal is to achieve the processing power of a single neuron of a human brain on a single PC. Interactions with billions of other computers should achieve human-level intelligence (AGI).
Pdsampler.jl 28 ⭐
Piecewise Deterministic Sampler library (Bouncy particle sampler, Zig Zag sampler, ...)
Paramonte 63 ⭐
ParaMonte: Plain Powerful Parallel Monte Carlo and MCMC Library for Python, MATLAB, Fortran, C++, C.
Ipynotebook_machinelearning 25 ⭐
This contains a number of IP[y]: Notebooks that hopefully give a light to areas of bayesian machine learning.
Lowlevelparticlefilters.jl 26 ⭐
Simple particle/kalman filtering, smoothing and parameter estimation
Bnlearn 34 ⭐
Python package for learning the graphical structure of Bayesian networks, parameter learning, inference and sampling methods.
Dpmmsubclusters.jl 26 ⭐
Distributed MCMC Inference in Dirichlet Process Mixture Models (High Performance Machine Learning Workshop 2019)
Pymc Stochastic Process 24 ⭐
Demonstrating the benefits of using Bayesian Inference and PYMC3 for estimating the parameters of stochastic processes commonly used in quantitative finance.
Approxposterior 22 ⭐
A Python package for approximate Bayesian inference and optimization using Gaussian processes
Cgpm 22 ⭐
Library of composable generative population models which serve as the modeling and inference backend of BayesDB.
Embracinguncertainty 21 ⭐
Material for AMLD 2020 workshop "Bayesian Inference: embracing uncertainty"
Rhat_ess 19 ⭐
Rank-normalization, folding, and localization: An improved R-hat for assessing convergence of MCMC
Bayesiansvm 16 ⭐
Source code of the Bayesian SVM described in the paper by Wenzel et al. "Bayesian Nonlinear Support Vector Machines for Big Data"
Logdensityproblems.jl 17 ⭐
A common framework for implementing and using log densities for inference.
Kissabc.jl 17 ⭐
Pure julia implementation of Multiple Affine Invariant Sampling for efficient Approximate Bayesian Computation
Torsionfit 14 ⭐
Bayesian tools for fitting molecular mechanics torsion parameters to quantum chemical data.
Pydata Dc 2018 14 ⭐
@matthewbrems and I presented "Recreating, Understanding, and Visualizing FiveThirtyEight's Elections Forecast" at PyData DC 2018
Bayesian_cnn_continuallearning 14 ⭐
Interpreting Bayesian inference as continual learning with a CNN
Variational Item Response Theory Public 15 ⭐
A PyTorch implementation of "Variational Item Response Theory: Fast Accurate, and Expressive"
Bbsbayes 13 ⭐
An R Package for Hierarchical Bayesian Analysis of North American Breeding Bird Survey Data
Pycbcinferenceworkshopmay2019 12 ⭐
Repository for the PyCBC Inference workshop in Portsmouth, UK, 14 May - 16 May 2019.
Zigzagboomerang.jl 11 ⭐
Sleek implementations of the ZigZag, Boomerang and other assorted piecewise deterministic Markov processes for Markov Chain Monte Carlo
Vi_vae_gmm 11 ⭐
Variational Inference/Variational AutoEncoder + Gaussian Mixtures implementation in zhusuan
Mcmc Estimation Of Stochastic Differential Equations Papers 11 ⭐
A list (quite disorganized for now) of papers tackling the Bayesian estimation of Ito processes (and their discrete time version)
Massivedatans 10 ⭐
Big Data vs. complex physical models - a scalable nested sampling inference algorithm for many data sets