yinjiangjin

ASN

bertviz

Tool for visualizing attention in the Transformer model (BERT and OpenAI GPT-2)

byteps

A high performance and general PS framework for distributed training

CMAE

cmarl_ame

Implementation of ICLR'23 publication "Certifiably Robust Policy Learning against Adversarial Multi-Agent Communication".

CommNet-BiCnet

CommNet and BiCnet implementation in tensorflow

Corel5K

这是Corel5K图像集，共包含科雷尔（Corel）公司收集整理的5000幅图片，故名：Corel5K，童鞋们可用于科学图像实验：分类、检索等。Corel5k数据集是图像实验的事实标准数据集。请勿用于商业用途。私底下学习交流使用。 Corel图像库是科雷尔（Corel）公司收集整理的较为丰富的图像库涵盖多个主题。Corel图像库由若干个CD组成，每个CD包含100张大小相等的图像，可以转换成多种格式。每张CD代表一个语义主题，例如有公共汽车、恐龙、海滩等。 Corel5k自从被提出用于图像标注实验后，已经成为图像实验的标准数据集，被广泛应用于标注算法性能的比较。Corel5k由50张CD组成，包含50个语义主题。 Corel5k图像库通常被分成三个部分： 4000张图像作为训练集，500张图像作为验证集用来估计模型参数，其余500张作为测试集评价算法性能。使用验证集寻找到最优模型参数后4000张训练集和500张验证集混合起来组成新的训练集。 该图像库中的每张图片被标注1~5个标注词，训练集中总共有374个标注词，在测试集中总共使用了263个标注词。 童鞋们自己去提取相关低层视觉特征：Rgb Lab Hsv Sift Gist HOG等等。 童鞋们完成 svm knn adaboost 逻辑回归 随机森林 mimlsvm mimlknn mimlboost 自定义算法 等等多类与多标签实验吧。Go, ...

Decision_Tree

在西瓜数据集2.0上基于信息增益准则生成决策树

deeplearningbook-chinese

Deep Learning Book Chinese Translation

DeepRL

【深度强化学习社区】一个资料与学习内容最全的服务平台

yinjiangjin/ASN

yinjiangjin/CMAE

yinjiangjin/cmarl_ame

Implementation of ICLR'23 publication "Certifiably Robust Policy Learning against Adversarial Multi-Agent Communication".

yinjiangjin/Decision_Tree

在西瓜数据集2.0上基于信息增益准则生成决策树

yinjiangjin/DeepRL

【深度强化学习社区】一个资料与学习内容最全的服务平台

yinjiangjin/dual-policy-distillation

yinjiangjin/elf

yinjiangjin/HiT-MAC

This repository is the official implementation of Learning Multi-Agent Coordination for Enhancing Target Coverage in Directional Sensor Networks.

yinjiangjin/liir

yinjiangjin/MAAC

Code for "Actor-Attention-Critic for Multi-Agent Reinforcement Learning" ICML 2019

yinjiangjin/marl_demo

demo of multi-agent reinforcement learning algorithms, such as ATT-MADDPG and NCC-MARL.

yinjiangjin/MERL

yinjiangjin/Multi-Agent-Communication-Considering-Representation-Learning

yinjiangjin/multiagent_mujoco

Benchmark for Continuous Multi-Agent Robotic Control, based on OpenAI's Mujoco Gym environments.

yinjiangjin/NDQ

Codes accompanying the paper "Learning Nearly Decomposable Value Functions with Communication Minimization" (ICLR 2020)

yinjiangjin/netron

Visualizer for neural network, deep learning and machine learning models

yinjiangjin/open_spiel

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

yinjiangjin/PIC

PIC: Permutation Invariant Critic for Multi-Agent Deep Reinforcement Learning

yinjiangjin/reinforcement-learning

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

yinjiangjin/Reinforcement-Learning-in-Robotics

This is a private learning repository for reinforcement learning techniques used in robotics.

yinjiangjin/RF-WISE

RF-Wise is the first work to collect the fine-grained CSI-like sensing features from the RFID signal.

yinjiangjin/SARNet

yinjiangjin/ShadowSocksShare

Python爬虫/Flask网站/免费ShadowSocks帐号/ssr订阅/json API

yinjiangjin/sllurp

Pure-Python client for LLRP-based RFID readers

yinjiangjin/SQDDPG

This is a framework for the research on multi-agent reinforcement learning and the implementation of the experiments in the paper titled by ''Shapley Q-value: A Local Reward Approach to Solve Global Reward Games''.

yinjiangjin/StarCraft

Implementations of QMIX, VDN and COMA on SMAC, corresponding papers are "QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning", "Value-Decomposition Networks For Cooperative Multi-Agent Learning", and "Counterfactual Multi-Agent Policy Gradients".

yinjiangjin/tensor2tensor

Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.

yinjiangjin/tensorlayer

Deep Learning and Reinforcement Learning Library for Scientists

yinjiangjin/tfpyth

Putting TensorFlow back in PyTorch, back in TensorFlow (differentiable TensorFlow PyTorch adapters).

yinjiangjin/TMC

Pytorch implementation of "Succinct and Robust Multi-Agent Communication With Temporal Message Control"