Popular GitHub Repositories for Matrix Factorization

Easy-to-use,Modular and Extendible package of deep-learning based CTR models .

A Python scikit for building and analyzing recommender systems

Cross-platform chatbot framework made with love

A Python implementation of LightFM, a hybrid recommendation algorithm.

High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.

Deep recommender models using PyTorch.

High-efficiency floating-point neural network inference operators for mobile, server, and Web

Recommender Learning with Tensorflow2.x

[CVPR 2021] Official PyTorch implementation for Transformer Interpretability Beyond Attention Visualization, a novel method to visualize classifications by Transformer based networks.

Acceleration package for neural networks on multi-core CPUs

TensorLy: Tensor Learning in Python.

A fast, ergonomic and portable tensor library in Nim with a deep learning focus for CPU, GPU and embedded devices via OpenMP, Cuda and OpenCL backends

A super fast Graph Database uses GraphBLAS under the hood for its sparse adjacency matrix graph representation. Our goal is to provide the best Knowledge Graph for LLM (GraphRAG).

PyTorch Extension Library of Optimized Autograd Sparse Matrix Operations

Factorization Machine models in PyTorch

Programmable CUDA/C++ GPU Graph Analytics

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 Comparative Framework for Multimodal Recommender Systems

CTR prediction models based on deep learning(基于深度学习的广告推荐CTR预估模型)

A parallel implementation of "graph2vec: Learning Distributed Representations of Graphs" (MLGWorkshop 2017).