Graph Classification On Neuron Binary
Metrics
Accuracy
Results
Performance results of various models on this benchmark
Model Name | Accuracy | Paper Title | Repository |
|---|---|---|---|
| PI-PL | 84.1 | Persistence Images: A Stable Vector Representation of Persistent Homology | - |
| WKPI-kcenters | 86.5 | Learning metrics for persistence-based summaries and applications for graph classification | - |
| PWGK | 80.1 | Kernel method for persistence diagrams via kernel embedding and weight factor | - |
| WKPI-kmeans | 90.3 | Learning metrics for persistence-based summaries and applications for graph classification | - |
| SW | 85.1 | Sliced Wasserstein Kernel for Persistence Diagrams | - |
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