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Benchmarks
Hypergraph Node Classification on NTU 2012 (test)
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75.06
Accuracy
HyperGCL (A6: proposed generative augmentation)
70.536
71.7105
72.885
74.0595
Oct 7, 2022
Accuracy
Updated 4d ago
Evaluation Results
Method
Method
Links
Accuracy
HyperGCL (A6: proposed generative augmentation)
Attack Type=Random, Tr...
2022.10
75.06
HyperGCL (A2: generalized hyperedge augmentation)
Attack Type=Random, Tr...
2022.10
74.5
HyperGCL (A6: proposed generative augmentation)
Attack Type=Net, Train...
2022.10
74.37
HyperGCL (A2: generalized hyperedge augmentation)
Attack Type=Net, Train...
2022.10
73.86
SetGNN
Attack Type=Random, Tr...
2022.10
73.84
HyperGCL (A4: feature perturbation)
Attack Type=Random, Tr...
2022.10
73.73
HyperGCL (A4: feature perturbation)
Attack Type=Net, Train...
2022.10
73.72
SetGNN
Attack Type=Net, Train...
2022.10
73.38
HyperGCL (A6: proposed generative augmentation)
Attack Type=Minmax, Tr...
2022.10
72.09
HyperGCL (A2: generalized hyperedge augmentation)
Attack Type=Minmax, Tr...
2022.10
71.4
HyperGCL (A4: feature perturbation)
Attack Type=Minmax, Tr...
2022.10
71.06
SetGNN
Attack Type=Minmax, Tr...
2022.10
70.71
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