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Benchmarks
Hypergraph Node Classification on ModelNet40 (test)
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96.58
Accuracy
HyperGCL (A6: proposed generative augmentation)
93.2
94.0775
94.955
95.8325
Oct 7, 2022
Accuracy
Updated 4d ago
Evaluation Results
Method
Method
Links
Accuracy
HyperGCL (A6: proposed generative augmentation)
Attack Type=Random, Tr...
2022.10
96.58
HyperGCL (A6: proposed generative augmentation)
Attack Type=Net, Train...
2022.10
96.23
HyperGCL (A2: generalized hyperedge augmentation)
Attack Type=Random, Tr...
2022.10
96.09
HyperGCL (A4: feature perturbation)
Attack Type=Random, Tr...
2022.10
95.79
SetGNN
Attack Type=Random, Tr...
2022.10
95.74
HyperGCL (A2: generalized hyperedge augmentation)
Attack Type=Net, Train...
2022.10
95.52
HyperGCL (A4: feature perturbation)
Attack Type=Net, Train...
2022.10
95.44
SetGNN
Attack Type=Net, Train...
2022.10
95.41
HyperGCL (A6: proposed generative augmentation)
Attack Type=Minmax, Tr...
2022.10
94.82
HyperGCL (A2: generalized hyperedge augmentation)
Attack Type=Minmax, Tr...
2022.10
93.64
HyperGCL (A4: feature perturbation)
Attack Type=Minmax, Tr...
2022.10
93.35
SetGNN
Attack Type=Minmax, Tr...
2022.10
93.33
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