hexiangnan
Professor with University of Science and Technology of China (USTC)
University of Science and Technology of China (USTC)China
hexiangnan's Stars
recommenders-team/recommenders
Best Practices on Recommendation Systems
hexiangnan/neural_collaborative_filtering
Neural Collaborative Filtering
wubinzzu/NeuRec
Next RecSys Library
xiangwang1223/knowledge_graph_attention_network
KGAT: Knowledge Graph Attention Network for Recommendation, KDD2019
xiangwang1223/neural_graph_collaborative_filtering
Neural Graph Collaborative Filtering, SIGIR2019
kuandeng/LightGCN
eBay/KPRN
Reasoning Over Knowledge Graph Paths for Recommendation
TaoMiner/joint-kg-recommender
SAI990323/TALLRec
duxy-me/ConvNCF
Experimental codes for paper "Outer Product-based Neural Collaborative Filtering".
leibinghe/GAAL-based-outlier-detection
GAAL-based Outlier Detection
Wuyxin/DIR-GNN
Official code of "Discovering Invariant Rationales for Graph Neural Networks" (ICLR 2022)
fajieyuan/WSDM2019-nextitnet
Generative model for sequential recommendation based on Convolution Neural Networks (CNN))
linzh92/DeepICF
TensorFlow Implementation of Deep Item-based Collaborative Filtering Model for Top-N Recommendation
HaojiHu/TIFUKNN
kNN-based next-basket recommendation
weitianxin/MACR
[KDD 2021] Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System
yihong-chen/lambda-opt
Pytorch implementation of λOpt: Learn to Regularize Recommender Models in Finer Levels, KDD 2019
chenboability/CFM
xinxin-me/RCF
Tensorflow implementation of RCF
Qcactus/CPR
TensorFlow implementation of our paper: Cross Pairwise Ranking for Unbiased Item Recommendation (WWW'22)
dingjingtao/ReinforceNS
duxy-me/AMR
This is our official implementation for the paper: Jinhui Tang, Xiaoyu Du, Xiangnan He, Fajie Yuan, Qi Tian, and Tat-Seng Chua, Adversarial Training Towards Robust Multimedia Recommender System.
XinyuGuan01/Attentive-Aspect-based-Recommendation-Model
HaojiHu/Sets2Sets
Sequential sets to sequential sets learning
will-ww/IntroDaSE
《数据科学与工程导论》教材配套资源
haoyanbin918/Group-Contextualization
[CVPR22] Group Contextualization for Video Recognition
zyang1580/DCR
This is an implementation for our paper "Addressing Confounding Feature Issue for Causal Recommendation" based on PyTorch.
zzhUSTC2016/TIDE
fulifeng/Cross-GCN
Cross-GCN: Enhancing Graph Convolutional Network with k-Order Feature Interactions
lsh0520/AFISM
APR enhances the pairwise ranking method BPR by performing adversarial training. To illustrate how it works, APR on FISM is implemented here by adding adversarial perturbations on the matrices P and Q.