JavierAntoran/Bayesian-Neural-Networks

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

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kumar-shridhar/PyTorch-BayesianCNN

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

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lucadellalib/bdl-rul-svgd

Bayesian deep learning for remaining useful life estimation via Stein variational gradient descent

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lucadellalib/bayestorch

Lightweight Bayesian deep learning library for fast prototyping based on PyTorch

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konstantinos-p/Bayesian-Neural-Networks-Reading-List

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"

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FedericoVasile1/bayesian-cnn

Comparison of a network implemented via Variational Inference with the same network implemented via Monte Carlo Dropout

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Feuermagier/Beyond_Deep_Ensembles

Code for the paper "Beyond Deep Ensembles: A Large-Scale Evaluation of Bayesian Deep Learning under Distribution Shift"

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nitarshan/bayes-by-backprop 📦

PyTorch implementation of "Weight Uncertainty in Neural Networks"

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mjpyeon/pytorch-bayes-by-backprop

PyTorch implementation of "Weight Uncertainties in Neural Networks" (Bayes-by-Backprop)

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gozsoy/bayes-by-backprop

PyTorch implementation of the paper 'Weight Uncertainty in Neural Networks'

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fangyuan-ksgk/Bayesian-Neural-Network

Pytorch implementation of Bayes by Backprop from scratch.

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asajatovic/bayesian-deep-learning-text-classification

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