Variational Inference

PyMCPython

Bayesian Modeling and Probabilistic Programming in Python

pyroPython

A flexible, scalable deep probabilistic programming library built on PyTorch for universal probabilistic modeling.

pyroPython

A flexible, scalable deep probabilistic programming library built on PyTorch for universal representation of computable probability distributions.

OryxJupyter Notebook

A library for probabilistic reasoning and statistical analysis integrated with TensorFlow and JAX.

NumPyroPython

A lightweight probabilistic programming library using NumPy and JAX for autograd and JIT compilation to GPU/TPU/CPU.

sklearn-bayesJupyter Notebook

A Python package providing Bayesian machine learning algorithms with a scikit-learn compatible API.

PyVarInfPython

A Python package for training PyTorch neural networks using variational inference for Bayesian deep learning.

kalman-jaxJupyter Notebook

A JAX-based framework for approximate inference in Markov Gaussian processes using iterated Kalman smoothing.

Generative Modeling Explained

A statistical machine learning tutorial explaining key generative models like diffusion, energy-based, VAE, and GAN models with intuitive analogies.