Machine learning, in numpy

Bayesian Modeling and Probabilistic Programming in Python

Deep universal probabilistic programming with Python and PyTorch

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.

Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.

Fast and Easy Infinite Neural Networks in Python

A Python library that helps data scientists to infer causation rather than observing correlation.

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

Bayesian Data Analysis course at Aalto

Bayesian inference with probabilistic programming.

PyMC educational resources

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

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

Awesome resources on normalizing flows.

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

brms R package for Bayesian generalized multivariate non-linear multilevel models using Stan

solution of exercises of the book "probabilistic robotics"

BAyesian Model-Building Interface (Bambi) in Python.

Welcome to the Physics-based Deep Learning Book v0.3 - the GenAI Edition

RStan, the R interface to Stan