fuxianh Goto Github PK

reinforcement-learning

Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.

reinforcement-learning-an-introduction

Python Implementation of Reinforcement Learning: An Introduction

reinforcement-learning-with-tensorflow

Simple Reinforcement learning tutorials

reinspect

End to end detection in crowded scenes

renzhengfei

任正非**

rl-cc

Web-based Reinforcement Learning Control Center

rllab

rllab is a framework for developing and evaluating reinforcement learning algorithms, fully compatible with OpenAI Gym.

rlpaperlist

Personal Repo to keep track of RL papers

rl_a3c_pytorch

Reinforcement learning A3C LSTM Atari with Pytorch

sac

Soft Actor-Critic

shadowsocks-android

A shadowsocks client for Android

siamese

siamfc-tf

State-of-the-art object tracking at high framerates, in TensorFlow.

simhash-py

Simhash and near-duplicate detection

snn4hrl

Stochastic Neural Networks for Hierarchical Reinforcement Learning

starcraft1

starcraft with reinforcement learning

state-marginal-matching

statistical-learning-method_code

手写实现李航《统计学习方法》书中全部算法

super-mario-bros-a3c-pytorch

Asynchronous Advantage Actor-Critic (A3C) algorithm for Super Mario Bros

td3

PyTorch implementation of TD3 and DDPG for OpenAI gym tasks

tensorflow

Computation using data flow graphs for scalable machine learning

tensorflow-

Tensorflow实战学习笔记、代码、机器学习进阶系列

tensorflow-examples

TensorFlow Tutorial and Examples for beginners

tensorflow_learning_notes

tensorflow学习笔记，来源于电子书：《Tensorflow实战Google深度学习框架》

tensorpack

A Neural Net Training Interface on TensorFlow, with focus on speed + flexibility

tfusion

CVPR2018: Unsupervised Cross-dataset Person Re-identification by Transfer Learning of Spatio-temporal Patterns

thubeamer

tsinghuabeamer.template

tianshou

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

torchcraft

Connecting Torch to StarCraft

unreal

Reinforcement learning with unsupervised auxiliary tasks