There are 23 repositories under matrix-factorization topic.
Book_4_《矩阵力量》 | 鸢尾花书:从加减乘除到机器学习;上架!
LibRec: A Leading Java Library for Recommender Systems, see
Deep recommender models using PyTorch.
A curated list of community detection research papers with implementations.
LAPACK development repository
An Open-source Toolkit for Deep Learning based Recommendation with Tensorflow.
Fast Clojure Matrix Library
A Comparative Framework for Multimodal Recommender Systems
This is the repository of our article published in RecSys 2019 "Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches" and of several follow-up studies.
A parallel implementation of "graph2vec: Learning Distributed Representations of Graphs" (MLGWorkshop 2017).
Low-Rank and Sparse Tools for Background Modeling and Subtraction in Videos
TOROS Buffalo: A fast and scalable production-ready open source project for recommender systems
Nimfa: Nonnegative matrix factorization in Python
Official code for "DaisyRec 2.0: Benchmarking Recommendation for Rigorous Evaluation" (TPAMI2022) and "Are We Evaluating Rigorously? Benchmarking Recommendation for Reproducible Evaluation and Fair Comparison" (RecSys2020)
Armadillo: fast C++ library for linear algebra & scientific computing - https://arma.sourceforge.net
pytorch version of neural collaborative filtering
recommender system library for the CLR (.NET)
A Comprehensive Framework for Building End-to-End Recommendation Systems with State-of-the-Art Models
[ICLR 2021 top 3%] Is Attention Better Than Matrix Decomposition?
NMFLibrary: Non-negative Matrix Factorization (NMF) Library: Version 2.1
A PyTorch Implementation of "Watch Your Step: Learning Node Embeddings via Graph Attention" (NeurIPS 2018).
PyTorch Implementations For A Series Of Deep Learning-Based Recommendation Models
Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation
The TensorFlow reference implementation of 'GEMSEC: Graph Embedding with Self Clustering' (ASONAM 2019).
Recommender system and evaluation framework for top-n recommendations tasks that respects polarity of feedbacks. Fast, flexible and easy to use. Written in python, boosted by scientific python stack.
Graph Embedding Evaluation / Code and Datasets for "Graph Embedding on Biomedical Networks: Methods, Applications, and Evaluations" (Bioinformatics 2020)
recommender system tutorial with Python
A highly-modularized and recommendation-efficient recommendation library based on PyTorch.