WEGL

Reported on 5 benchmarks across 3 tasks · 1 paper

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

Graphs3 results

Graph ClassificationonREDDIT-B
Accuracy· 2020-06-16
92
best: 93.15 (CRaWl)
Wasserstein Embedding for Graph Learning arXiv:2006.09430
Graph ClassificationonENZYMES
Accuracy· 2020-06-16
60.5
best: 78.39 (DSGCN-allfeat)
Wasserstein Embedding for Graph Learning arXiv:2006.09430
Graph Property Predictiononogbg-molhiv
Number of params· 2020-06-16
361064
best: 47183040 (Graphormer)
Wasserstein Embedding for Graph Learning arXiv:2006.09430

Methodology2 results

ClassificationonREDDIT-B
Accuracy· 2020-06-16
92
best: 93.15 (CRaWl)
Wasserstein Embedding for Graph Learning arXiv:2006.09430
ClassificationonENZYMES
Accuracy· 2020-06-16
60.5
best: 78.39 (DSGCN-allfeat)
Wasserstein Embedding for Graph Learning arXiv:2006.09430