CmdStanR: the R interface to CmdStan

A collection of Bayesian data analysis recipes using PyMC3

Generative Models Tutorial with Demo: Bayesian Classifier Sampling, Variational Auto Encoder (VAE), Generative Adversial Networks (GANs), Popular GANs Architectures, Auto-Regressive Models, Important Generative Model Papers, Courses, etc..

Scalable inference for a generative model of astronomical images

Bayesian Changepoint Detection

Statistical Rethinking (2nd Ed) with Tensorflow Probability

Python package for Bayesian Machine Learning with scikit-learn API

GPstuff - Gaussian process models for Bayesian analysis

Bayesian Data Analysis demos for Python

Boltzmann Machines in TensorFlow with examples

Understanding normalizing flows

Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"

PyTorch implementation of "Weight Uncertainty in Neural Networks"

Statistical Rethinking (2nd ed.) with NumPyro

Collection of probabilistic models and inference algorithms

A U-Net combined with a variational auto-encoder that is able to learn conditional distributions over semantic segmentations.

How to do Bayesian statistical modelling using numpy and PyMC3

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

Deep universal probabilistic programming with Python and PyTorch

The RadioTalk dataset of talk radio transcripts