Papers with Code 아카이브

Collaborative Filtering

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하위 태스크

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평가표

4

보존된 평가 기록

30

코드

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

https://github.com/damicoedoardo/igccf

공식 코드

Item Graph Convolution Collaborative Filtering for Inductive Recommendations

https://github.com/damicoedoardo/psge

공식 코드

Pure Spectral Graph Embeddings: Reinterpreting Graph Convolution for Top-N Recommendation

https://github.com/danialebrat/lusifer

공식 코드

Lusifer: LLM-based User SImulated Feedback Environment for online Recommender systems

https://github.com/davidzwz/cde-cf

공식 코드

Graph Neural Controlled Differential Equations For Collaborative Filtering

https://github.com/dawenl/expo-mf

공식 코드

Modeling User Exposure in Recommendation

https://github.com/dawenl/vae_cf

공식 코드

Variational Autoencoders for Collaborative Filtering

https://github.com/deezer/concept_hierarchy

공식 코드

Explainability in Music Recommender Systems

https://github.com/deezer/recsys21-hlr

공식 코드

Hierarchical Latent Relation Modeling for Collaborative Metric Learning

https://github.com/deezer/uncertainty_feedback

공식 코드

Uncertainty in Repeated Implicit Feedback as a Measure of Reliability

https://github.com/digitalTranshumant/WikiRecNet-ComplexRec2020

공식 코드

Scalable Recommendation of Wikipedia Articles to Editors Using Representation Learning

https://github.com/domkowald/fairrecsys

공식 코드

Popularity Bias in Collaborative Filtering-Based Multimedia Recommender Systems

https://github.com/downeykking/l2cl

공식 코드

L^2CL: Embarrassingly Simple Layer-to-Layer Contrastive Learning for Graph Collaborative Filtering

https://github.com/dshakes90/Last-fm-Gender-Bias-Analysis

공식 코드

Exploring Artist Gender Bias in Music Recommendation

https://github.com/duxy-me/ConvNCF

공식 코드

Outer Product-based Neural Collaborative Filtering

https://github.com/echo740/DANSER-WWW-19

공식 코드

Dual Graph Attention Networks for Deep Latent Representation of Multifaceted Social Effects in Recommender Systems

https://github.com/edervishaj/ganmf

공식 코드

GAN-based Matrix Factorization for Recommender Systems

https://github.com/enoche/SelfCF

공식 코드

SelfCF: A Simple Framework for Self-supervised Collaborative Filtering

https://github.com/enoche/dgvae

공식 코드

Disentangled Graph Variational Auto-Encoder for Multimodal Recommendation with Interpretability

https://github.com/ethanhezhao/NBVAE

공식 코드

Variational Autoencoders for Sparse and Overdispersed Discrete Data

https://github.com/evfro/HyperbolicRecommenders

공식 코드

Performance of Hyperbolic Geometry Models on Top-N Recommendation Tasks

https://github.com/evfro/kdd2018

공식 코드

HybridSVD: When Collaborative Information is Not Enough

https://github.com/facebookresearch/StarSpace

공식 코드

StarSpace: Embed All The Things!

https://github.com/facebookresearch/dlrm

공식 코드

Mixed Dimension Embeddings with Application to Memory-Efficient Recommendation Systems

https://github.com/fangshuheng/hire

공식 코드

All-in-One: Heterogeneous Interaction Modeling for Cold-Start Rating Prediction

https://github.com/fernandobperezm/an-evaluation-of-GAN-for-CF

공식 코드

An Evaluation Study of Generative Adversarial Networks for Collaborative Filtering

https://github.com/ferortega/bernoulli-matrix-factorization

공식 코드

Providing reliability in Recommender Systems through Bernoulli Matrix Factorization

https://github.com/ferortega/cf4j

공식 코드

CF4J: Collaborative Filtering for Java

https://github.com/fjssharpsword/BayesianRS

공식 코드

Probabilistic Latent Factor Model for Collaborative Filtering with Bayesian Inference

https://github.com/fmonti/mgcnn

공식 코드

Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks

https://github.com/fstrub95/Autoencoders_cf

공식 코드

Hybrid Collaborative Filtering with Autoencoders

https://github.com/fuxiailab/r-adjnorm

공식 코드

Investigating Accuracy-Novelty Performance for Graph-based Collaborative Filtering

https://github.com/g-h-li/idfree

공식 코드

From ID-based to ID-free: Rethinking ID Effectiveness in Multimodal Collaborative Filtering Recommendation

https://github.com/garfieldcat1985/ugrec

공식 코드

UGRec: Modeling Directed and Undirected Relations for Recommendation

https://github.com/georgeguo-cn/dualvae

공식 코드

DualVAE: Dual Disentangled Variational AutoEncoder for Recommendation

https://github.com/ghdtjr/a-llmrec

공식 코드

Large Language Models meet Collaborative Filtering: An Efficient All-round LLM-based Recommender System

https://github.com/giamba95/saplingsimilarity

공식 코드

Sapling Similarity: a performing and interpretable memory-based tool for recommendation

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