A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch

A toolbox for inference of mixture models

Probabilistic unsupervised feature extraction from seismic spectrograms for machine learning.

Fitting molecular Energies, Forces and Chemical shifts and Chemical Discovery with Scalable Gaussian Processes by Stochastic Variational Inference

Fast implementation of DAP topic model using Conjugate Computation Variational Inference

Novel technique to fit a target distribution with a class of distributions using SVI (via NumPyro). Unlike standard SVI, our "data" is a distribution rather than a finite collection of samples.

Summary notebook implementing Bayesian Model Averaging with numpyro.

Bayesian inference on logistic regression model

A Pyro-PPL implementation of a 2D Ornstein-Uhlenbeck process using stochastic variational inference.