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Models/R-GCN

R-GCN

Reported on 9 benchmarks across 1 task · 2 papers · 5 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Graphs9 results

  • Node ClassificationonMDGENRE
    Accuracy· 2022-03-04
    67.33
    SOTA
    R-GCN: The R Could Stand for RandomarXiv:2203.02424
  • Node ClassificationonAIFB
    Accuracy· 2017-03-17
    95.83
    SOTA
    Modeling Relational Data with Graph Convolutional NetworksarXiv:1703.06103
  • Node ClassificationonMUTAG
    Accuracy· 2017-03-17
    73.23
    best: 91.17 (BoP)
    SOTA
    Modeling Relational Data with Graph Convolutional NetworksarXiv:1703.06103
  • Node ClassificationonAM
    Accuracy· 2017-03-17
    89.29
    best: 92.41 (BoP)
    SOTA
    Modeling Relational Data with Graph Convolutional NetworksarXiv:1703.06103
  • Node ClassificationonBGS
    Accuracy· 2017-03-17
    83.1
    best: 92.41 (SCENE)
    SOTA
    Modeling Relational Data with Graph Convolutional NetworksarXiv:1703.06103
  • Node ClassificationonAMPLUS
    Accuracy· 2022-03-04
    83.81
    best: 84.54 (RR-GCN-PPV)
    R-GCN: The R Could Stand for RandomarXiv:2203.02424
  • Node ClassificationonDBLP
    Accuracy· 2022-03-04
    68.51
    best: 70.61 (RR-GCN-PPV)
    R-GCN: The R Could Stand for RandomarXiv:2203.02424
  • Node ClassificationonDMGFULL
    Accuracy· 2022-03-04
    57.52
    best: 63.38 (RR-GCN-PPV)
    R-GCN: The R Could Stand for RandomarXiv:2203.02424
  • Node ClassificationonDMG777K
    Accuracy· 2022-03-04
    62.51
    best: 63.97 (RR-GCN-PPV)
    R-GCN: The R Could Stand for RandomarXiv:2203.02424