Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
deep-learning
reproducible-research
regression
pytorch
uncertainty
classification
uncertainty-neural-networks
bayesian-inference
mcmc
variational-inference
hmc
bayesian-neural-networks
langevin-dynamics
approximate-inference
local-reparametrization-trick
kronecker-factored-approximation
mc-dropout
bayes-by-backprop
out-of-distribution-detection
sgld
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Updated
May 1, 2020 - Jupyter Notebook