Stars
[NeurIPS'24] The source code for "Beyond Redundancy: Information-aware Unsupervised Multiplex Graph Structure Learning".
Awesome Easy-to-Use Deep Time Series Modeling based on PaddlePaddle, including comprehensive functionality modules like TSDataset, Analysis, Transform, Models, AutoTS, and Ensemble, etc., supportin…
PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）
GraphMAE: Self-Supervised Masked Graph Autoencoders in KDD'22
A PyTorch implementation of the Relational Graph Convolutional Network (RGCN).
A comprehensive (masked) graph autoencoders benchmark.
[KDD 2023] What’s Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders
[AAAI'25 Oral] The official implementation code of LLMEmb
Python implementation of "Item2Vec: Neural Item Embedding for Collaborative Filtering"
A Pytorch implementation of Collaborative Metric Learning (CML)
PyTorch Implementation of "BPR: Bayesian Personalized Ranking from Implicit Feedback"
PyTorch Implementation for Neural Graph Collaborative Filtering
CoNet: Collaborative Cross Networks for Cross-Domain Recommendation
"SemiSupervised for Cross-Domain Recommendation to Cold-Start Users"
A machine learning project that aims to predict the likelihood of a patient being readmitted to the hospital within 30 days of discharge
Aim of medical imaging is to capture abnormalities using image processing and machine learning techniques.
推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search.
An Embedding and Mapping framework for Cross-Domain Recommendation.
RecDCL: Dual Contrastive Learning for Recommendation (WWW'24, Oral)
Disentagnled Graph Collaborative Filtering, SIGIR2020
Neural Collaborative Filtering