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JavierAntoran
Bayesian-Neural-Networks JavierAntoran
303
1.9k
mit
28
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
hmc mcmc sgld pytorch mc-dropout regression uncertainty deep-learning classification bayes-by-backprop langevin-dynamics bayesian-inference approximate-inference reproducible-research variational-inference bayesian-neural-networks uncertainty-neural-networks local-reparametrization-trick out-of-distribution-detection kronecker-factored-approximation
Created 2019-03-11
86 commits to master branch, last one about a year ago
konstantinos-p
Bayesian-Neural-Networks-Reading-List konstantinos-p
4
51
unknown
2
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 ...
hmc mcmc sgld uncertainty deep-learning bayes-by-backprop langevin-dynamics bayesian-inference approximate-inference variational-inference bayesian-neural-networks uncertainty-neural-networks local-reparametrization-trick kronecker-factored-approximation
Created 2023-01-16
18 commits to main branch, last one about a year ago