Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization

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

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

Bayesian Deep Learning Benchmarks

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

Bayesian Deep Learning: A Survey

Building a Bayesian deep learning classifier

Sparse Variational Dropout, ICML 2017

Master Thesis on Bayesian Convolutional Neural Network using Variational Inference

PyTorch implementation of "Weight Uncertainty in Neural Networks"

Official implementation of "Evaluating Scalable Bayesian Deep Learning Methods for Robust Computer Vision", CVPR Workshops 2020.

In which I try to demystify the fundamental concepts behind Bayesian deep learning.

MLSS2019 Tutorial on Bayesian Deep Learning

[MedIA Best Paper Award] Official implementation of MedIA paper "BayeSeg: Bayesian Modelling for Medical Image Segmentation with Interpretable Generalizability"

(ICML 2022) Official PyTorch implementation of “Blurs Behave Like Ensembles: Spatial Smoothings to Improve Accuracy, Uncertainty, and Robustness”.

Structured Bayesian Pruning, NIPS 2017

Bayesian Graph Neural Networks with Adaptive Connection Sampling - Pytorch

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

Code to accompany the paper 'Improving model calibration with accuracy versus uncertainty optimization'.

Uncertainty Guided Progressive GANs for Medical Image Translation