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adversarial-attacks-pytorch

PyTorch implementation of adversarial attacks.

awesome-latex-drawing

Drawing Bayesian networks, graphical models, tensors, and technical frameworks and illustrations in LaTeX.

awesome-learning-with-label-noise

A curated list of resources for Learning with Noisy Labels

awesome-self-supervised-learning

A curated list of awesome self-supervised methods

badnets-pytorch

Simple PyTorch implementations of Badnets on MNIST and CIFAR10.

boolean_composition

Code for the paper "A Boolean Task Algebra For Reinforcement Learning"

cla_demo

Demo code for a clustering-based label-aware autoencoder

composition

Code for the paper "Composing Value Functions in Reinforcement Learning"

conal

Code for AAAI 2021 long paper Learning from Crowds by Modeling Common Confusions.

cpu

《自己动手写CPU》

dads

Code for 'Dynamics-Aware Unsupervised Discovery of Skills' (DADS). Enables skill discovery without supervision, which can be combined with model-based control.

data

deep-reinforcement-learning-algorithms-with-pytorch

PyTorch implementations of deep reinforcement learning algorithms and environments

deep_laa

dm_control

DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.

fuzzy-data-fusion

garage

A toolkit for reproducible reinforcement learning research.

hindsight-experience-replay

This is the pytorch implementation of Hindsight Experience Replay (HER) - Experiment on all fetch robotic environments.

learning-independent-skills

Task dependent skill transformation is challenging due to the ignorance of the relationships between primitive skills. In this project, we propose a skill decomposition algorithm to learn independent skills, which are more suitable than primitive skills for task dependent skill transformation.

new_york_weather

nsfc-latex

paper-reading

比做算法的懂工程落地，比做工程的懂算法模型。

ptan

PyTorch Agent Net: reinforcement learning toolkit for pytorch

pytorch-vae

A Collection of Variational Autoencoders (VAE) in PyTorch.

questioning-strategy-classification

Repository for AM207 final project

raylab

Reinforcement learning algorithms in RLlib

rllab-curriculum

softlearning

Softlearning is a reinforcement learning framework for training maximum entropy policies in continuous domains. Includes the official implementation of the Soft Actor-Critic algorithm.

softqlearning

SoftQ Implementation

spinningup-workspace

Reading notes & PyTorch experiments on OpenAI's "Spinning Up in DRL" tutorial.