Popular GitHub Repositories for Bayesian Neural Networks

Awesome resources on normalizing flows.

A simple and extensible library to create Bayesian Neural Network layers on PyTorch.

Master Thesis on Bayesian Convolutional Neural Network using Variational Inference

Gaussian Processes for Experimental Sciences

Lightning-UQ-Box: Uncertainty Quantification for Neural Networks with PyTorch and Lightning

Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"

A Tensorflow implementation of "Bayesian Graph Convolutional Neural Networks" (AAAI 2019).

PyTorch Implementations of Dropout Variants

Pytorch implementation of Variational Dropout Sparsifies Deep Neural Networks

Fully and Partially Bayesian Neural Nets

Code for the paper Implicit Weight Uncertainty in Neural Networks

TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".

Bayesian Graph Neural Networks with Adaptive Connection Sampling - Pytorch

A pytorch implementation of MCDO(Monte-Carlo Dropout methods)

Code for "BayesAdapter: Being Bayesian, Inexpensively and Robustly, via Bayeisan Fine-tuning"

Natural Gradient, Variational Inference

Comparison of Variational Autoencoders with Bayesian Neural Networks. Accuracy, Latent space, Reconstruction and White Noise filtering.

On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification

ComBiNet: Compact Convolutional Bayesian Neural Network for Image Segmentation

Deep Probabilistic Programming Examples in Pytorch using pyro