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GitHub topics: kronecker-factored-approximation

lixilinx/psgd_torch

Pytorch implementation of preconditioned stochastic gradient descent (Kron and affine preconditioner, low-rank approximation preconditioner and more)

Language: Python - Size: 3.08 MB - Last synced at: 5 days ago - Pushed at: 5 days ago - Stars: 175 - Forks: 11

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).

Language: Python - Size: 5.91 MB - Last synced at: 17 days ago - Pushed at: about 3 years ago - Stars: 3,766 - Forks: 836

JavierAntoran/Bayesian-Neural-Networks

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

Language: Jupyter Notebook - Size: 15.6 MB - Last synced at: 23 days ago - Pushed at: over 1 year ago - Stars: 1,893 - Forks: 308

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"

Size: 82 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 29 - Forks: 2