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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