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Models/PNA

PNA

Reported on 6 benchmarks across 5 tasks · 1 paper · 5 SOTA

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

Graphs5 results

  • Graph RegressiononZINC
    MAE· 2020-04-12
    0.142
    best: 0.051 (ESA + rings + NodeRWSE + EdgeRWSE)
    SOTA
    Principal Neighbourhood Aggregation for Graph NetsarXiv:2004.05718
  • Graph ClassificationonCIFAR10 100k
    Accuracy (%)· 2020-04-12
    70.47
    best: 76.468 (GRIT)
    SOTA
    Principal Neighbourhood Aggregation for Graph NetsarXiv:2004.05718
  • Node ClassificationonPATTERN 100k
    Accuracy (%)· 2020-04-12
    86.567
    best: 86.816 (EGT)
    SOTA
    Principal Neighbourhood Aggregation for Graph NetsarXiv:2004.05718
  • Graph Property Predictiononogbg-molpcba
    Number of params· 2020-04-12
    6550839
    best: 119529665 (HIG(pre-trained on PCQM4M))
    SOTA
    Principal Neighbourhood Aggregation for Graph NetsarXiv:2004.05718
  • Graph Property Predictiononogbg-molhiv
    Number of params· 2020-04-12
    326081
    best: 47183040 (Graphormer)
    Principal Neighbourhood Aggregation for Graph NetsarXiv:2004.05718

Methodology1 result

  • ClassificationonCIFAR10 100k
    Accuracy (%)· 2020-04-12
    70.47
    best: 76.468 (GRIT)
    SOTA
    Principal Neighbourhood Aggregation for Graph NetsarXiv:2004.05718