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

Deep probabilistic analysis of single-cell and spatial omics data

Complex-valued neural networks for pytorch and Variational Dropout for real and complex layers.

Official Pytorch code for (AAAI 2020) paper "Capsule Routing via Variational Bayes", https://arxiv.org/pdf/1905.11455.pdf

Single-cell Hierarchical Poisson Factorization

Clustering with variational Bayes and population Monte Carlo

Dimensionality reduction of spikes trains

Model for learning document embeddings along with their uncertainties

A simple library to run variational inference on Stan models.

Low-variance, efficient and unbiased gradient estimation for optimizing models with binary latent variables. (ICLR 2019)

This repository is for sharing the scripts of EM algorithm and variational bayes.

A toolbox for inference of mixture models

The sparse Bayesian learning sandbox

Variational Joint Filtering

[Pytorch] Minimal implementation of a Variational Autoencoder (VAE) with Categorical Latent variables inspired from "Categorical Reparameterization with Gumbel-Softmax".

JAX version of vLGP (github.com/catniplab/vlgp)

Implementation and derivation of "Variational Bayesian inference for a nonlinear forward model." [Chappell et al. 2008] for arbitrary, user-defined model errors.

Expectation Maximisation, Variational Bayes, ARD, Loopy Belief Propagation, Gaussian Process Regression

implement machine learning models from scratch

Cross-center smoothness prior for Bayesian image segmentation