blue-wx

styleguide

Style guides for Google-originated open-source projects

TD3

Author's PyTorch implementation of TD3 for OpenAI gym tasks

PPO-Continuous-Pytorch

A clean and robust Pytorch implementation of PPO on continuous action space.

gpt_academic

为GPT/GLM等LLM大语言模型提供实用化交互接口，特别优化论文阅读/润色/写作体验，模块化设计，支持自定义快捷按钮&函数插件，支持Python和C++等项目剖析&自译解功能，PDF/LaTex论文翻译&总结功能，支持并行问询多种LLM模型，支持chatglm3等本地模型。接入通义千问, deepseekcoder, 讯飞星火, 文心一言, llama2, rwkv, claude2, moss等。

SpaceSim

baselines

OpenAI Baselines: high-quality implementations of reinforcement learning algorithms

OpenAI_Five_vs_Dota2_Explained

This is the code for "OpenAI Five vs DOTA 2 Explained" By Siraj Raval on Youtube

on-policy

This is the official implementation of Multi-Agent PPO (MAPPO).

PPOxFamily

PPO x Family DRL Tutorial Course（决策智能入门级公开课：8节课帮你盘清算法理论，理顺代码逻辑，玩转决策AI应用实践 ）

orbitdeterminator

determination of satellite orbits and more

Hands-On-Meta-Learning-With-Python

Learning to Learn using One-Shot Learning, MAML, Reptile, Meta-SGD and more with Tensorflow

Machine-Learning-is-ALL-You-Need

🔥🌟《Machine Learning 格物志》: ML + DL + RL basic codes and notes by sklearn, PyTorch, TensorFlow, Keras & the most important, from scratch!💪 This repository is ALL You Need!

awesome_deep_learning_interpretability

深度学习近年来关于神经网络模型解释性的相关高引用/顶会论文(附带代码)

interpretable-ml-book

Book about interpretable machine learning

awesome-machine-learning-interpretability

A curated list of awesome responsible machine learning resources.

xinzhibei_rationale_competition_2022

2022 兴智杯 -- 深度学习模型可解释性 -- 第三名（二等奖）

dissect

深度卷积神经网络分类器的可解释性研究

Visual-analytics-and-Interpretability-in-Deep-Learning

本项目主要是通过可视分析的手段，对深度学习的可解释性做出讨论与探讨。并且记录小组成员的学习过程与工作

InterpretableMLBook

《可解释的机器学习--黑盒模型可解释性理解指南》，该书为《Interpretable Machine Learning》中文版

derl

Code for "Embodied Intelligence via Learning and Evolution", Gupta et al, Nature Communications

Deep-CFR

Scalable Implementation of Deep CFR and Single Deep CFR

PromptCraft-Robotics

Community for applying LLMs to robotics and a robot simulator with ChatGPT integration

Counterfactual_Regret_Minimization_Python

Counterfactual Regret Minimization (CFR) sample code in Python

annotated_deep_learning_paper_implementations

🧑‍🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

regret-matching

Simple implementation of regret matching algorithm for RPS nash equilibrium computation via self-play

rebel

An algorithm that generalizes the paradigm of self-play reinforcement learning and search to imperfect-information games.

go-cfr

go-cfr implements several forms of Counter Factual Regret minimization in Golang

open_spiel

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

game_theory

These are some MATLAB implementations of functions related to Game Thory such as MinMax, Nash and Backwards Induction, which are applied in some exercises.

TuGames

A Mathematica Package for Cooperative Game Theory