Alternatives and similar repositories for InvCF

Users that are interested in InvCF are comparing it to the libraries listed below

• THUwangcy / DirectAU
  KDD'2022: Towards Representation Alignment and Uniformity in Collaborative Filtering
  ☆67Updated 2 years ago
• weiwei1206 / CML
  The implementation of Contrastive Meta Learning with Behavior Multiplicity forRecommendation
  ☆47Updated 7 months ago
• anzhang314 / BC-Loss
  Official code of "Incorporating Bias-aware Margins into Contrastive Loss for Collaborative Filtering" (2022 NeurIPS)
  ☆22Updated 2 years ago
• cjx96 / DisenCDR
  [SIGIR 2022]DisenCDR: Learning Disentangled Representations for Cross-Domain Recommendation
  ☆38Updated 3 years ago
• cjx96 / CDRIB
  [ICDE 2022]Cross-Domain Recommendation to Cold-Start Users via Variational Information Bottleneck
  ☆31Updated 2 years ago
• TiliaceaeSU / PBAT
  Code for MM'23 paper "Personalized Behavior-Aware Transformer for Multi-Behavior Sequential Recommendation"
  ☆29Updated last year
• cjx96 / C2DSR
  [CIKM 2022]Contrastive Cross-Domain Sequential Recommendation
  ☆36Updated 2 years ago
• HKUDS / SimRec
  [WWW'23] "SimRec: Graph-less Collaborative Filtering"
  ☆32Updated 2 years ago
• HKUDS / AutoCF
  [WWW'23] "AutoCF: Automated Self-Supervised Learning for Recommendation"
  ☆49Updated last year
• Chain123 / CAT-ART
  One for All, All for One: Learning and Transferring User Embeddings for Cross-Domain Recommendation (WSDM-2023)
  ☆36Updated 10 months ago
• HKUDS / DCRec
  [WWW'2023] "DCRec: Debiased Contrastive Learning for Sequential Recommendation"
  ☆59Updated 2 years ago
• ChangxinTian / RGCF
  [SIGIR'22] Official PyTorch implementation for "Learning to Denoise Unreliable Interactions for Graph Collaborative Filtering".
  ☆16Updated 2 years ago
• yimutianyang / SIGIR2021-EGLN
  The implement of papar "Enhanced Graph Learning for Collaborative Filtering via Mutual Information Maximization"
  ☆18Updated 3 years ago
• rlqja1107 / MELT
  Official PyTorch implementation Source code for MELT: Mutual Enhancement of Long-Tailed User and Item for Sequential Recommendation, acce…
  ☆36Updated last year
• junkangwu / Adap_tau
  [WWW 2023] Official code of "Adap-$\tau$: Adaptively Modulating Embedding Magnitude for Recommendation"
  ☆29Updated last year
• Applied-Machine-Learning-Lab / PLATE
  implementation code for 'PLATE: A Prompt-Enhanced Paradigm for Multi-Scenario Recommendations' in SIGIR 2023
  ☆13Updated 8 months ago
• wenqifan03 / GTN-SIGIR2022
  Graph Trend Filtering Networks for Recommendations, SIGIR'2022
  ☆25Updated 3 years ago
• WenjieWWJ / DenoisingRec
  Adaptive Denoising Training (ADT) for Recommendation.
  ☆71Updated 3 years ago
• HKUDS / MAERec
  [SIGIR'2023] "MAERec: Graph Masked Autoencoder for Sequential Recommendation"
  ☆62Updated 2 years ago
• WujiangXu / AMID
  The code for WWW2024 paper "Rethinking Cross-Domain Sequential Recommendation under Open-World Assumptions".
  ☆31Updated 9 months ago
• KingGugu / TiCoSeRec
  Official source code for AAAI 2023 paper: Uniform Sequence Better: Time Interval Aware Data Augmentation for Sequential Recommendation
  ☆61Updated 3 weeks ago
• lqfarmer / CCDR
  ☆23Updated 2 years ago
• zfan20 / MStein
  WWW 2023 "Mutual Wasserstein Discrepancy Minimization for Sequential Recommendation"
  ☆16Updated last year
• Arthurma71 / AdvDrop
  ☆10Updated last year
• anananan116 / MBGen
  [CIKM '24] Implementation of "Multi-Behavior Generative Recommendation"
  ☆35Updated 9 months ago
• liuqidong07 / DiffuASR
  [CIKM'23] The official implementation code of DiffuASR.
  ☆38Updated last year
• Woeee / FMLP-Rec
  The source code for WWW 2022 Paper "Filter-enhanced MLP is All You Need for Sequential Recommendation"
  ☆45Updated 3 years ago
• layer6ai-labs / HGCF
  Code for the WWW'21 paper "HGCF: Hyperbolic Graph Convolution Networks for Collaborative Filtering"
  ☆51Updated 3 years ago
• HKUDS / DCCF
  [SIGIR'2023] "DCCF: Disentangled Contrastive Collaborative Filtering"
  ☆58Updated last year
• enoche / BM3
  Pytorch implementation for "Bootstrap Latent Representations for Multi-modal Recommendation"-WWW'23
  ☆57Updated last year