coderhaohao's Stars
apache/pulsar
Apache Pulsar - distributed pub-sub messaging system
Htallone/JBUAA
北航学报自然科学版LaTeX模板(非官方)
leiurayer/downkyi
哔哩下载姬downkyi,哔哩哔哩网站视频下载工具,支持批量下载,支持8K、HDR、杜比视界,提供工具箱(音视频提取、去水印等)。
dennybritz/reinforcement-learning
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
Curt-Park/rainbow-is-all-you-need
Rainbow is all you need! A step-by-step tutorial from DQN to Rainbow
datawhalechina/easy-rl
强化学习中文教程(蘑菇书🍄),在线阅读地址:https://datawhalechina.github.io/easy-rl/
NeuronDance/DeepRL
Deep Reinforcement Learning Lab, a platform designed to make DRL technology and fun for everyone
cristianoc20/RL_learning
ljpzzz/machinelearning
My blogs and code for machine learning. http://cnblogs.com/pinard
harvardnlp/annotated-transformer
An annotated implementation of the Transformer paper.
graykode/nlp-tutorial
Natural Language Processing Tutorial for Deep Learning Researchers
hongleizhang/RSPapers
A Curated List of Must-read Papers on Recommender System.
shenweichen/DeepCTR
Easy-to-use,Modular and Extendible package of deep-learning based CTR models .
chang2000/tfGMN
Graph Matching Networks for Learning the Similarity of Graph Structured Objects
Zziwei/Heater--Cold-Start-Recommendation
Code for the SIGIR20 paper -- Recommendation for New Users and New Items via Randomized Training and Mixture-of-Experts Transformation
cnclabs/smore
SMORe: Modularize Graph Embedding for Recommendation
recommenders-team/recommenders
Best Practices on Recommendation Systems
librahu/HIN-Datasets-for-Recommendation-and-Network-Embedding
Heterogeneous Information Network Datasets for Recommendation and Network Embedding
ChenglongChen/tensorflow-DeepFM
Tensorflow implementation of DeepFM for CTR prediction.
ngduyanhece/neuMF
lixin4ever/Conference-Acceptance-Rate
Acceptance rates for the major AI conferences
twjiang/graphSAGE-pytorch
A PyTorch implementation of GraphSAGE. This package contains a PyTorch implementation of GraphSAGE.
GraphSAINT/GraphSAINT
[ICLR 2020; IPDPS 2019] Fast and accurate minibatch training for deep GNNs and large graphs (GraphSAINT: Graph Sampling Based Inductive Learning Method).
williamleif/GraphSAGE
Representation learning on large graphs using stochastic graph convolutions.
google-research/google-research
Google Research
Tiiiger/SGC
official implementation for the paper "Simplifying Graph Convolutional Networks"
Diego999/pyGAT
Pytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)
coderhaohao/pytorch_geometric
Geometric Deep Learning Extension Library for PyTorch
NVIDIA/nvidia-docker
Build and run Docker containers leveraging NVIDIA GPUs
pyg-team/pytorch_geometric
Graph Neural Network Library for PyTorch