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PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) ...
Created
2017-08-22
274 commits to master branch, last one 3 years ago
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
Pytorch implementation of preconditioned stochastic gradient descent (Kron and affine preconditioner, low-rank approximation preconditioner and more)
Created
2018-04-07
168 commits to master branch, last one a day ago
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 ...
Created
2023-01-16
18 commits to main branch, last one about a year ago