yangyi0318

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》

yangyi0318/adversarial-attacks-pytorch

PyTorch implementation of adversarial attacks.

yangyi0318/awesome-latex-drawing

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

yangyi0318/Awesome-Learning-with-Label-Noise

A curated list of resources for Learning with Noisy Labels

yangyi0318/awesome-self-supervised-learning

A curated list of awesome self-supervised methods

yangyi0318/badnets-pytorch

Simple PyTorch implementations of Badnets on MNIST and CIFAR10.

yangyi0318/boolean_composition

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

yangyi0318/cla_demo

Demo code for a clustering-based label-aware autoencoder

yangyi0318/composition

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

yangyi0318/CoNAL

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

yangyi0318/cpu

《自己动手写CPU》

yangyi0318/dads

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

yangyi0318/Deep-Reinforcement-Learning-Algorithms-with-PyTorch

PyTorch implementations of deep reinforcement learning algorithms and environments

yangyi0318/deep_laa

yangyi0318/dm_control

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

yangyi0318/fuzzy-data-fusion

yangyi0318/garage

A toolkit for reproducible reinforcement learning research.

yangyi0318/hindsight-experience-replay

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

yangyi0318/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.

yangyi0318/NSFC-LaTex

yangyi0318/paper-reading

比做算法的懂工程落地，比做工程的懂算法模型。

yangyi0318/ptan

PyTorch Agent Net: reinforcement learning toolkit for pytorch

yangyi0318/PyTorch-VAE

A Collection of Variational Autoencoders (VAE) in PyTorch.

yangyi0318/raylab

Reinforcement learning algorithms in RLlib

yangyi0318/rllab-curriculum

yangyi0318/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.

yangyi0318/SoftQLearning

SoftQ Implementation

yangyi0318/spinningup-workspace

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

yangyi0318/stable-baselines3

PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

yangyi0318/Stein-Variational-Gradient-Descent

code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"

yangyi0318/Tabular-RL-with-Python

Tabular Reinforcement Learning Algorithms with NumPy & Visualizations with Seaborn