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ikostrikov
pytorch-a2c-ppo-acktr-gail ikostrikov
831
3.5k
mit
67
PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) ...
a2c ale ppo kfac acktr atari mujoco hessian pytorch roboschool actor-critic second-order deep-learning natural-gradients continuous-control advantage-actor-critic reinforcement-learning deep-reinforcement-learning proximal-policy-optimization kronecker-factored-approximation
Created 2017-08-22
274 commits to master branch, last one 2 years ago
JavierAntoran
Bayesian-Neural-Networks JavierAntoran
299
1.8k
mit
27
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 8 months ago
konstantinos-p
Bayesian-Neural-Networks-Reading-List konstantinos-p
2
39
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 7 months ago