There are 1 repository under bayes-by-backprop topic.
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.
PyTorch implementation of "Weight Uncertainty in Neural Networks"
A primer on Bayesian Neural Networks. The aim of this reading list is to facilitate the entry of new researchers into the field of Bayesian Deep Learning, by providing an overview of key papers. More details: "A Primer on Bayesian Neural Networks: Review and Debates"
Code for the paper "Beyond Deep Ensembles: A Large-Scale Evaluation of Bayesian Deep Learning under Distribution Shift"
Bayesian deep learning for remaining useful life estimation via Stein variational gradient descent
PyTorch implementation of "Weight Uncertainties in Neural Networks" (Bayes-by-Backprop)
Lightweight Bayesian deep learning library for fast prototyping based on PyTorch
Comparison of a network implemented via Variational Inference with the same network implemented via Monte Carlo Dropout
Pytorch implementation of Bayes by Backprop from scratch.
PyTorch implementation of the paper 'Weight Uncertainty in Neural Networks'