Papers with Code 아카이브

Collaborative Filtering

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하위 태스크

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평가표

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보존된 평가 기록

30

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/jasonsun0310/MatrixCompletion.jl

Matrix Completion from Noisy Entries

https://github.com/jaywonchung/BERT4Rec-VAE-Pytorch

Variational Autoencoders for Collaborative Filtering

https://github.com/jeongwhanchoi/LT-OCF-Tutorial

LT-OCF: Learnable-Time ODE-based Collaborative Filtering

https://github.com/johnnyjana730/MVIN

RippleNet: Propagating User Preferences on the Knowledge Graph for Recommender Systems

https://github.com/jongpillee/deep-content-user

Deep Content-User Embedding Model for Music Recommendation

https://github.com/jowoojun/collaborative_filtering_keras

Hybrid Recommender System based on Autoencoders

https://github.com/jsleroux/Recommender-Systems

Neural Collaborative Filtering

https://github.com/jstol/neural-net-matrix-factorization

Neural Network Matrix Factorization

https://github.com/jvbalen/autoencoders_cf

Variational Autoencoders for Collaborative Filtering

https://github.com/kartikey-singh/Replicating-SeER

SeER: An Explainable Deep Learning MIDI-based Hybrid Song Recommender System

https://github.com/kihongmin/NCF

Neural Collaborative Filtering

https://github.com/kushagramahajan/GraphRegMC-scRNAseq

Matrix Completion on Graphs

https://github.com/leoentersthevoid/ncf

Neural Collaborative Filtering

https://github.com/lijm1358/NCF_FoursquareDataset_Test

Neural Collaborative Filtering

https://github.com/liu-jc/PyTorch_NGCF

Neural Graph Collaborative Filtering

https://github.com/lixinso/recommender_system_a_survey

Neural Collaborative Filtering

https://github.com/louis-monier/recommendation_engine

A Contextual-Bandit Approach to Personalized News Article Recommendation

https://github.com/lt610/DAGNN

Neural Graph Collaborative Filtering

https://github.com/lucapantea/LightGCN

LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation

https://github.com/madansinghal/graphranko

Neural Graph Collaborative Filtering

https://github.com/manohar029/Ecommerce-Implicit-Data-Recommender-System

Personalizing Similar Product Recommendations in Fashion E-commerce

https://github.com/marlesson/recsys_autoencoders

Training Deep AutoEncoders for Collaborative Filtering

https://github.com/massquantity/LibRecommender

Item2Vec: Neural Item Embedding for Collaborative Filtering

https://github.com/melissakou/KG-RecSys

Learning over Knowledge-Base Embeddings for Recommendation

https://github.com/microsoft/recai

Knowledge Plugins: Enhancing Large Language Models for Domain-Specific Recommendations

https://github.com/microsoft/recommenders

Neural Collaborative Filtering

https://github.com/mindspore-ai/contrib/tree/master/application/GTE

How Expressive are Graph Neural Networks in Recommendation?

https://github.com/mindspore-ai/contrib/tree/master/papers/DiffNet%2B%2B

DiffNet++: A Neural Influence and Interest Diffusion Network for Social Recommendation

https://github.com/mindspore-ai/models/tree/master/official/recommend/ncf

Neural Collaborative Filtering

https://github.com/mkfilipiuk/VAE-CF

Variational Autoencoders for Collaborative Filtering

https://github.com/mostsuperman/KGCN-ML

Knowledge Graph Convolutional Networks for Recommender Systems

https://github.com/mostsuperman/test

Knowledge Graph Convolutional Networks for Recommender Systems

https://github.com/myungkeun-cho/taobao_dlrm

Mixed Dimension Embeddings with Application to Memory-Efficient Recommendation Systems

https://github.com/nathann3/better_than_netflix_movie_recommender

A Hybrid Variational Autoencoder for Collaborative Filtering

https://github.com/nikithamalgifb/dlrm

Mixed Dimension Embeddings with Application to Memory-Efficient Recommendation Systems

https://github.com/nnkkmto/item2vec-food-rec

Item2Vec: Neural Item Embedding for Collaborative Filtering

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.