John's repositories
Awesome-Deep-Learning-Papers-for-Search-Recommendation-Advertising
Awesome Deep Learning papers for industrial Search, Recommendation and Advertising. They focus on Embedding, Matching, Ranking (CTR and CVR prediction), Post Ranking, Multi-task Learning, Graph Neural Networks, Transfer Learning, Reinforcement Learning, Self-supervised Learning and so on.
ComiRec
Source code and dataset for KDD 2020 paper "Controllable Multi-Interest Framework for Recommendation"
euler
A distributed graph deep learning framework.
galileo
Galileo library for large scale graph training by JD
GJC1203
Config files for my GitHub profile.
RepCONC
Learning Discrete Representations via Constrained Clustering for Effective and Efficient Dense Retrieval (WSDM'22)
SSGC
Implementation for Simple Spectral Graph Convolution in ICLR 2021
tensor2tensor
Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.