woithook

woithook's Stars

• jayelm/emergent-generalization

  Emergent Communication of Generalizations, NeurIPS 2021

  Language:Python131

• DmitryRyumin/AAAI-2024-Papers

  AAAI 2024 Papers: Explore a comprehensive collection of innovative research papers presented at one of the premier artificial intelligence conferences. Seamlessly integrate code implementations for better understanding. ⭐ experience the forefront of progress in artificial intelligence with this repository!

  Language:Python26214

• Nandaka/PixivUtil2

  Download images from Pixiv and more!

  Language:Python2.3k250

• LeoMax-Xiong/bookshelf

  :books: books

  378

• Stability-AI/generative-models

  Generative Models by Stability AI

  Language:Python23.2k2.6k

• google-deepmind/emergent_communication_at_scale

  Language:Python325

• jacobandreas/tre

  Measuring compositionality in representation learning

  Language:Jupyter Notebook696

• game-reverse/IrisMysteria-Translate

  爱丽丝圣礼全汉化补丁-梦之圣礼汉化组+台服翻译

  221

• google-research/football

  Check out the new game server:

  Language:Python3.3k1.3k

• bkgoksel/emergent-language

  An implementation of Emergence of Grounded Compositional Language in Multi-Agent Populations by Igor Mordatch and Pieter Abbeel

  Language:Python7023

• openai/multiagent-particle-envs

  Code for a multi-agent particle environment used in the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"

  Language:Python2.3k785

• google-deepmind/open_spiel

  OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.

  Language:C++4.1k897

• oxwhirl/pymarl

  Python Multi-Agent Reinforcement Learning framework

  Language:Python1.8k377

• RomainPastureau/Reservoir-Jupyter

  Reservoir computing sous Jupyter

  Language:Jupyter Notebook911

• SciML/ReservoirComputing.jl

  Reservoir computing utilities for scientific machine learning (SciML)

  Language:Julia20436

• g1910/HyperNetworks

  PyTorch implementation of HyperNetworks (Ha et al., ICLR 2017) for ResNet (Residual Networks)

  Language:Python25038

• tengyuma/cs229m_notes

  Language:TeX20242

• learnables/learn2learn

  A PyTorch Library for Meta-learning Research

  Language:Python2.6k348

• tristandeleu/pytorch-meta

  A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch

  Language:Python2k253

• metaopt/torchopt

  TorchOpt is an efficient library for differentiable optimization built upon PyTorch.

  Language:Python50835

• tristandeleu/pytorch-maml-rl

  Reinforcement Learning with Model-Agnostic Meta-Learning in Pytorch

  Language:Python804156

• cbfinn/maml_rl

  Code for RL experiments in "Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks"

  Language:Python605180

• p-christ/Deep-Reinforcement-Learning-Algorithms-with-PyTorch

  PyTorch implementations of deep reinforcement learning algorithms and environments

  Language:Python5.5k1.2k

• danieltan07/learning-to-reweight-examples

  PyTorch Implementation of the paper Learning to Reweight Examples for Robust Deep Learning

  Language:Jupyter Notebook35161

• vwxyzjn/cleanrl

  High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)

  Language:Python4.8k559

• IandRover/meta_gradient_RL

  Implementation of NeurIPS 2018 paper "Meta-Gradient Reinforcement Learning"

  Language:Jupyter Notebook142

• qfettes/DeepRL-Tutorials

  Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch

  Language:Jupyter Notebook1k327

• sweetice/Deep-reinforcement-learning-with-pytorch

  PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....

  Language:Python3.7k836

• LI-Yanting/CFR

  This is the course project of MVA-Reinforcement Learning of 2017, Counterfactual Regret Minimization

  Language:Jupyter Notebook21

• ZhiruiFeng/Counterfactual_RL

  Reinforcement Learning Agent that can make full use of counterfactual information.

  Language:Python3