This is our implementation of ENMF: Efficient Neural Matrix Factorization (TOIS. 38, 2020). This also provides a fair evaluation of existing state-of-the-art recommendation models.

The code repository for the paper: Peijie et al., Neighborhood-Enhanced Supervised Contrastive Learning for Collaborative Filtering. IEEE TKDE, 2023.

用pytorch 方法复现了二十多个经典的推荐算法论文，其中包含排序论文和推荐召回论文，并在demo里面选了一个召回模型和排序模型的运行示例。

Source code for the RecSys 2024 paper "Revisiting LightGCN: Unexpected Inflexibility, Inconsistency, and A Remedy Towards Improved Recommendation."

A movie recommendation system utilizing a Graph Neural Network (GNN) framework implemented in Jupyter Notebook

Implementation of various collaborative filtering methods for recommender systems with implicit feedback

RecSys Codes based on PyTorch

Comparative Analysis of Recommender Systems on Goodreads Data: A study benchmarking SVD, SVAE, NGCF, and LightGCN models to understand their efficacy in book recommendation.