Pytorch domain library for recommendation systems

An index of recommendation algorithms that are based on Graph Neural Networks. (TORS)

A box of core libraries for recommendation model development

推荐系统修炼手册

A curated model zoo for recommendation tasks

This is a repo containing recent papers related to temporal (sequential) recommender system

A framework for large scale recommendation algorithms.

links to conference publications in graph-based deep learning

Code for paper "Leaping Through Time with Gradient-based Adaptation for Recommendation", AAAI-2022.

TensorFlow implementation for paper Time Interval Aware Self-Attention for Sequential Recommendation.

Neural Graph Collaborative Filtering, SIGIR2019

Revisiting Graph based Collaborative Filtering: A Linear Residual Graph Convolutional Network Approach, AAAI2020

Deoscillated Graph Collaborative Filtering

PyTorch Implementation for Neural Graph Collaborative Filtering

A collection of resources for Recommender Systems (RecSys)

Code for the WWW'22 paper "MCL: Mixed-Centric Loss for Collaborative Filtering"

Disentagnled Graph Collaborative Filtering, SIGIR2020

The official implementation of "Disentangling User Interest and Conformity for Recommendation with Causal Embedding" (WWW '21)

MetaBalance algorithm for multi-task learning

Simple ranking metrics for PyTorch on CPU or GPU

TensorFlow implementation of our paper: Cross Pairwise Ranking for Unbiased Item Recommendation (WWW'22)

Heterogeneous Recommendation

This is a repository of public data sources for Recommender Systems (RS).