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Benchmarks
Graph-level classification on Synthetic temporal-graph dataset (full)
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94
Accuracy
GAT
13.5768
34.4559
55.335
76.2141
May 31, 2026
Accuracy
Macro F1
Updated 22h ago
Evaluation Results
Method
Method
Links
Accuracy
Macro F1
GAT
Features=pooled node e...
2026.05
94
93.98
RF
Features=motif feature...
2026.05
93.33
93.27
GCN
Features=pooled node e...
2026.05
92.67
92.61
SAGE
Features=pooled node e...
2026.05
91.67
91.45
SVM
Features=motif feature...
2026.05
80
79.48
GCN
Features=pooled node e...
2026.05
73.33
67.74
SAGE
Features=pooled node e...
2026.05
59.33
53.92
GAT
Features=pooled node e...
2026.05
16.67
4.76
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