Popular GitHub Repositories for Weight Factorization

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

A Python scikit for building and analyzing recommender systems

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.

MiniMax-M1, the world's first open-weight, large-scale hybrid-attention reasoning model.

Recommender Learning with Tensorflow2.x

PyTorch implementation of various methods for continual learning (XdG, EWC, SI, LwF, FROMP, DGR, BI-R, ER, A-GEM, iCaRL, Generative Classifier) in three different scenarios.

TensorLy: Tensor Learning in Python.

Factorization Machine models in PyTorch

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).

Jcseg is a light weight NLP framework developed with Java. Provide CJK and English segmentation based on MMSEG algorithm, With also keywords extraction, key sentence extraction, summary extraction implemented based on TEXTRANK algorithm. Jcseg had a build-in http server and search modules for lucene,solr,elasticsearch,opensearch

a pytorch lib with state-of-the-art architectures, pretrained models and real-time updated results

TensorFlow implementation of an arbitrary order Factorization Machine

OCTIS: Comparing Topic Models is Simple! A python package to optimize and evaluate topic models (accepted at EACL2021 demo track)

Trankit is a Light-Weight Transformer-based Python Toolkit for Multilingual Natural Language Processing

[NeurIPS 2024] BLAST: Block Level Adaptive Structured Matrix for Efficient Deep Neural Network Inference