Bayesian Open Source Projects

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.

Bayesian Modeling and Probabilistic Programming in Python

Deep universal probabilistic programming with Python and PyTorch

Python for《Deep Learning》，该书为《深度学习》(花书) 数学推导、原理剖析与源码级别代码实现

Bayesian optimization in PyTorch

Python Toolkit for Causal and Probabilistic Reasoning

Adaptive Experimentation Platform

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.

A python tutorial on bayesian modeling techniques (PyMC3)

Bayesian Data Analysis course at Aalto

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

Enhancing {ggplot2} plots with statistical analysis 📊📣

A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.

Notebooks about Bayesian methods for machine learning

An R package for causal inference in time series

A general-purpose probabilistic programming system with programmable inference

Exploratory analysis of Bayesian models with Python

Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).

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

Spearmint Bayesian optimization codebase

Probabilistic Modeling Toolkit for Matlab/Octave.

Spearmint is a package to perform Bayesian optimization according to the algorithms outlined in the paper: Practical Bayesian Optimization of Machine Learning Algorithms. Jasper Snoek, Hugo Larochelle and Ryan P. Adams. Advances in Neural Information Processing Systems, 2012

GemPy is an open-source, Python-based 3-D structural geological modeling software, which allows the implicit (i.e. automatic) creation of complex geological models from interface and orientation data. It also offers support for stochastic modeling to address parameter and model uncertainties.

BAyesian Model-Building Interface (Bambi) in Python.

:milky_way: The R easystats-project

Pythonic Bayesian Belief Network Package, supporting creation of and exact inference on Bayesian Belief Networks specified as pure python functions.

A Comparative Framework for Multimodal Recommender Systems

LightweightMMM 🦇 is a lightweight Bayesian Marketing Mix Modeling (MMM) library that allows users to easily train MMMs and obtain channel attribution information.

Seminars DeepBayes Summer School 2018

Bayesian Data Analysis demos for Python

Tensorflow code for the Bayesian GAN (https://arxiv.org/abs/1705.09558) (NIPS 2017)

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

JASP aims to be a complete statistical package for both Bayesian and Frequentist statistical methods, that is easy to use and familiar to users of SPSS

A simple and extensible library to create Bayesian Neural Network layers on PyTorch.

BayesDB on SQLite. A Bayesian database table for querying the probable implications of data as easily as SQL databases query the data itself.

Python/PyMC3 versions of the programs described in Doing bayesian data analysis by John K. Kruschke

An open source python library for scalable Bayesian optimisation.

A Bayesian database table for querying the probable implications of data as easily as SQL databases query the data itself. New implementation in http://github.com/probcomp/bayeslite

Use NLP to predict stock price movement associated with news

A list of resources for all invited talks, tutorials, workshops and presentations at NIPS 2017

Files for a tutorial to train SegNet for road scenes using the CamVid dataset

Visualizations of distributions and uncertainty

Python/PyMC3 port of the examples in " Statistical Rethinking A Bayesian Course with Examples in R and Stan" by Richard McElreath

TikZ library for drawing Bayesian networks, graphical models and (directed) factor graphs in LaTeX.

Deep Active Learning

Naive Bayesian Classification for Golang.

Example models for Stan

Methods to get the probability of a changepoint in a time series.

Python library for Multi-Armed Bandits

Bayesian analysis + tidy data + geoms (R package)

A general classifier module to allow Bayesian and LSI classifications.

:scroll: :tada: Automated reporting of objects in R

Bayesian Python: Bayesian inference tools for Python

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

Bayesian Analysis with Python (Second Edition)

How to do Bayesian statistical modelling using numpy and PyMC3

Bayesian Deep Learning Benchmarks

Awesome Multitask Learning Resources

A Python-based toolbox of various methods in decision making, uncertainty quantification and statistical emulation: multi-fidelity, experimental design, Bayesian optimisation, Bayesian quadrature, etc.

A curated list of resources dedicated to StarCraft AI.