caihuaiguang's Stars
GraphPKU/JacobiConv
How Powerful are Spectral Graph Neural Networks
GentleCP/UCAS-Helper
国科大(UCAS, ucas)校园网登录、课程资源下载、自动评教和分数查询助手
hrwhisper/algorithm_course
国科大 算法分析与设计 卜东波 作业答案整理(2016)
okcd00/CDSelector
UCAS Course Selector
liuch00/THU-Statistics-Record
这是本人统计学辅修课程的一些记录
weixr18/MLAN
A Note for Machine Learning Algorithms
MashPlant/undergraduate_projects
My undergraduate course projects in THU.
chiphuyen/machine-learning-systems-design
A booklet on machine learning systems design with exercises. NOT the repo for the book "Designing Machine Learning Systems"
OI-wiki/OI-wiki
:star2: Wiki of OI / ICPC for everyone. (某大型游戏线上攻略,内含炫酷算术魔法)
shaojintian/Best_README_template
🌩最好的中文README模板⚡️Best README template
pb0316/thuhole_memories
shengyp/doing_the_PhD
bugaosuni59/TH-CPL
清华大学计算机学科推荐学术会议和期刊列表
virginiakm1988/ML2022-Spring
**Official** 李宏毅 (Hung-yi Lee) 機器學習 Machine Learning 2022 Spring
mli/paper-reading
深度学习经典、新论文逐段精读
xuaikun/summary
总结相关经验
edge-video-services/ekya
Source code and datasets for Ekya, a system for continuous learning on the edge.
huangtinglin/MixGCF
MixGCF: An Improved Training Method for Graph Neural Network-based Recommender Systems, KDD2021
openmlsys/openmlsys-zh
《Machine Learning Systems: Design and Implementation》- Chinese Version
DropEdge/DropEdge
This is a Pytorch implementation of paper: DropEdge: Towards Deep Graph Convolutional Networks on Node Classification
LingxiaoShawn/PairNorm
Source code for PairNorm (ICLR 2020)
reczoo/BARS
BARS: Towards Open Benchmarking for Recommender Systems https://openbenchmark.github.io/BARS
reczoo/RecBox
A box of core libraries for recommendation model development
reczoo/RecZoo
A curated model zoo for recommendation tasks
edervishaj/GANMF
This is the repository for our paper "GAN-based Matrix Factorization for Recommender Systems" accepted at ACM/SIGAPP Symposium on Applied Computing (SAC '22).
hzwer/shareOI
算法竞赛课件分享
Vonng/ddia
《Designing Data-Intensive Application》DDIA中文翻译
ResidentMario/designing-data-intensive-applications-notes
Reading notes on the excellent "Designing Data-Intensive Applications"
ept/ddia-references
Literature references for “Designing Data-Intensive Applications”
alge24/ADA-UGNN
A Unified View on Graph Neural Networks as Graph Signal Denoising