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Models/Geom-GCN-P

Geom-GCN-P

Reported on 6 benchmarks across 1 task · 1 paper · 6 SOTA

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

Graphs6 results

Node ClassificationonWisconsin
Accuracy· 2020-02-13
64.12
best: 88.77 (MGNN + Hetero-S (6 layers))
SOTA
Geom-GCN: Geometric Graph Convolutional Networks arXiv:2002.05287
Node ClassificationonSquirrel
Accuracy· 2020-02-13
38.14
best: 57.83 (JKNet + Hetero-S (8 layers))
SOTA
Geom-GCN: Geometric Graph Convolutional Networks arXiv:2002.05287
Node ClassificationonTexas
Accuracy· 2020-02-13
67.57
best: 93.09 (MGNN + Hetero-S (8 layers))
SOTA
Geom-GCN: Geometric Graph Convolutional Networks arXiv:2002.05287
Node ClassificationonCornell
Accuracy· 2020-02-13
60.81
best: 82.4324 (FDGATII)
SOTA
Geom-GCN: Geometric Graph Convolutional Networks arXiv:2002.05287
Node ClassificationonChameleon
Accuracy· 2020-02-13
60.9
best: 70.18 (JKNet + Hetero-S (8 layers))
SOTA
Geom-GCN: Geometric Graph Convolutional Networks arXiv:2002.05287
Node ClassificationonActor
Accuracy· 2020-02-13
31.63
best: 35.99 (MGNN + Hetero-S (4 layers))
SOTA
Geom-GCN: Geometric Graph Convolutional Networks arXiv:2002.05287