Qiang He

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

Authors' implementation of PEER

Learning to Communicate with Deep Multi-Agent Reinforcement Learning in PyTorch

Pytorch Implementation of DQN / DDQN / Prioritized replay/ noisy networks/ distributional values/ Rainbow/ hierarchical RL

PyTorch implementations of Generative Adversarial Networks.

This repository contains most of classic deep reinforcement learning algorithms, including - DQN, DDQN, Dueling Network, DDPG, A3C, PPO, TRPO. (More algorithms are still in progress)

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The present anonymous repository serves as a guide for reproducing the results of the "BEER" method proposed in our ICLR submission "Adaptive Regularization of Representation Rank as an Implicit Constraint of Bellman Equation".

Anonymous code for ICML submission 45

2018/2019/校招/春招/秋招/算法/机器学习(Machine Learning)/深度学习(Deep Learning)/自然语言处理(NLP)/C/C++/Python/面试笔记

Code for POPO: Pessimistic Offline Policy Optimization

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Plotting of captured Tensorboard runs for seeded RL comparison

Virtual-Taobao simulators with OpenAI Gym interface

OpenAI Baselines: high-quality implementations of reinforcement learning algorithms

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

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A recipe for online RLHF.

An elegant, flexible, and superfast PyTorch deep Reinforcement Learning platform.

Inference code for LLaMA models

Official implementation of MEPE

Train transformer language models with reinforcement learning.

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Making large AI models cheaper, faster and more accessible

The simplest way to run LLaMA on your local machine

Code and documentation to train Stanford's Alpaca models, and generate the data.

Voltron: Language-Driven Representation Learning for Robotics

RWKV is a RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference, saves VRAM, fast training, "infinite" ctx_len, and free sentence embedding.

Implementation of Truncated Quantile Critics method for continuous reinforcement learning. https://bayesgroup.github.io/tqc/

A reusable framework for successor features for transfer in deep reinforcement learning using keras.

Code for the paper "Functional Regularization for Reinforcement Learning via Learned Fourier Features"

Public Repo for the paper "Overcoming The Spectral-Bias of Neural Value Approximation"

A PyTorch Library for Multi-Task Learning

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Codes for ICLR 21 paper: Neural Approximate Sufficient Statistics for Implicit Models

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Mirror Descent Policy Optimization

GULF: GUided Learning through successive Functional gradient optimization (author implementation of DPCNN included)

DrQ-v2: Improved Data-Augmented Reinforcement Learning

PyTorch Implementation of the Maximum a Posteriori Policy Optimisation

Collection of reinforcement learning algorithms

Code for ICLR 2019 paper "Adaptive Estimators Show Information Compression in Deep Neural Networks" (https://openreview.net/forum?id=SkeZisA5t7)

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Author's PyTorch implementation of TD3+BC, a simple variant of TD3 for offline RL

Codebase for Evolutionary Reinforcement Learning (ERL) from the paper "Evolution-Guided Policy Gradients in Reinforcement Learning" published at NeurIPS 2018

Code for "Proximal Distilled Evolutionary Reinforcement Learning", accepted at AAAI 2020

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Ameya's math and CS blog.

blog pages

CFG-GAN (Composite Functional Gradient learning of GAN) in pyTorch

Code for conservative Q-learning

Code for MOPO: Model-based Offline Policy Optimization

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Datasets for Data-Driven Deep Reinforcement Learning with Pybullet environments

Google Research

ICRL 2020

Code for Stabilizing Off-Policy RL via Bootstrapping Error Reduction

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PyTorch implementation of Distributed Distributional Deterministic Policy Gradients (https://arxiv.org/abs/1804.08617)

MINE: Mutual Information Neural Estimation in pytorch

PyTorch implementation of BCQ for "Off-Policy Deep Reinforcement Learning without Exploration"

Pytorch implementation of Neural Processes for functions and images :fireworks:

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aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

probmods 2: electric boogaloo

My continuously updated Machine Learning, Probabilistic Models and Deep Learning notes and demos (1000+ slides) 我不间断更新的机器学习，概率模型和深度学习的讲义(1000+页)和视频链接

ICML 2018 Self-Imitation Learning

Topics course Mathematics of Deep Learning, NYU, Spring 18

Code for visualizing the loss landscape of neural nets

Issues with Deep Learning of Aftershocks by DeVries

[ICML 2017] TensorFlow code for Curiosity-driven Exploration for Deep Reinforcement Learning

pytorch implementation of Curiosity-driven Exploration by Self-supervised Prediction

Code for the paper "Exploration by Random Network Distillation"

An OpenAI Gym interface to Super Mario Bros. & Super Mario Bros. 2 (Lost Levels) on The NES

This project explores deep reinforcement learning, hybrid actor-critic approach with A3C/PPO combined with curiosity for playing Super Mario Bros

Recommender Systems

Pytorch implementation of "FeUdal Networks for Hierarchical Reinforcement Learning" for Montezuma's Revenge

PyTorch implementation of Trust Region Policy Optimization

Modular Deep Reinforcement Learning framework in PyTorch.

Mirror of Stable-Baselines: a fork of OpenAI Baselines, implementations of reinforcement learning algorithms

Code for Go-Explore: a New Approach for Hard-Exploration Problems

Implementation of TRPO and related algorithms

A gallery for reinforcement learning, including frameworks, tutorials, papers, implementations, applications, etc.

TuShare is a utility for crawling historical data of China stocks

An educational resource to help anyone learn deep reinforcement learning.

Learning to Communicate with Deep Multi-Agent Reinforcement Learning

A complete and graceful API for Wechat. 微信个人号接口、微信机器人及命令行微信，三十行即可自定义个人号机器人。

Statistical learning methods, 统计学习方法 [李航] 值得反复读. [笔记, 代码, notebook, 参考文献, Errata]

PyTorch0.4 implementation of: actor critic / proximal policy optimization / acer / ddpg / twin dueling ddpg / soft actor critic / generative adversarial imitation learning / hindsight experience replay

Softlearning is a reinforcement learning framework for training maximum entropy policies in continuous domains.

PyTorch implementation of Deep Reinforcement Learning: Policy Gradient methods (TRPO, PPO, A2C) and Generative Adversarial Imitation Learning (GAIL). Fast Fisher vector product TRPO.

Code for reproducing results in "Glow: Generative Flow with Invertible 1x1 Convolutions"

Models and examples built with TensorFlow

VIP cheatsheets for Stanford's CS 229 Machine Learning

PyTorch implementation of TD3 and DDPG for OpenAI gym tasks

BY Blog ->

Paper list of multi-agent reinforcement learning (MARL)

Python Implementation of Reinforcement Learning: An Introduction

Predict survival on the Titanic

Example TensorFlow codes and Caicloud TensorFlow as a Service dev environment.

Computation using data flow graphs for scalable machine learning