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Models/ASAP

ASAP

Reported on 8 benchmarks across 2 tasks · 1 paper · 6 SOTA

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

Graphs4 results

Graph ClassificationonFRANKENSTEIN
Accuracy· 2019-11-18
66.26
best: 78.9 (GWL_WL)
SOTA
ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations arXiv:1911.07979
Graph ClassificationonNCI1
Accuracy· 2019-11-18
71.48
best: 73.5 (2-WL-GNN)
SOTA
ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations arXiv:1911.07979
Graph ClassificationonD&D
Accuracy· 2019-11-18
76.87
SOTA
ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations arXiv:1911.07979
Graph ClassificationonNCI109
Accuracy· 2019-11-18
70.07
best: 87.3 (WKPI-kcenters)
ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations arXiv:1911.07979

Methodology4 results

ClassificationonFRANKENSTEIN
Accuracy· 2019-11-18
66.26
best: 78.9 (GWL_WL)
SOTA
ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations arXiv:1911.07979
ClassificationonNCI1
Accuracy· 2019-11-18
71.48
best: 73.5 (2-WL-GNN)
SOTA
ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations arXiv:1911.07979
ClassificationonD&D
Accuracy· 2019-11-18
76.87
SOTA
ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations arXiv:1911.07979
ClassificationonNCI109
Accuracy· 2019-11-18
70.07
best: 87.3 (WKPI-kcenters)
ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations arXiv:1911.07979