kronecker-factored-approximation

There are 0 repository under kronecker-factored-approximation topic.

ikostrikov / pytorch-a2c-ppo-acktr-gail
PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).
pytorch reinforcement-learning deep-learning deep-reinforcement-learning actor-critic advantage-actor-critic a2c ppo proximal-policy-optimization acktr second-order hessian natural-gradients atari mujoco roboschool continuous-control kfac kronecker-factored-approximation ale
Language:Python 3469
JavierAntoran / Bayesian-Neural-Networks
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
deep-learning bayesian-inference pytorch reproducible-research bayesian-neural-networks bayes-by-backprop mc-dropout mcmc variational-inference kronecker-factored-approximation langevin-dynamics approximate-inference local-reparametrization-trick uncertainty uncertainty-neural-networks out-of-distribution-detection classification regression sgld hmc
Language:Jupyter Notebook 1742
konstantinos-p / Bayesian-Neural-Networks-Reading-List
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 details: "A Primer on Bayesian Neural Networks: Review and Debates"
approximate-inference bayes-by-backprop bayesian-inference bayesian-neural-networks deep-learning hmc kronecker-factored-approximation langevin-dynamics local-reparametrization-trick mcmc sgld uncertainty uncertainty-neural-networks variational-inference
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