PROTEINS
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Graph Classification | PROTEINS | Accuracy85.4 | 1,252 | |
| Graph Classification | PROTEINS (10-fold cross-validation) | Accuracy83.88 | 223 | |
| Graph Classification | PROTEINS (test) | Accuracy84.91 | 213 | |
| Graph Classification | PROTEINS | Classification Error Rate1.8 | 72 | |
| Virtual Screening | 100 Proteins | Median Percent Lift (Avg Top-10)32 | 45 | |
| Graph Classification | PROTEINS TUDataset | Accuracy90.3 | 44 | |
| Network Classification | PROTEINS | F1 Score79.46 | 35 | |
| Graph Classification | PROTEINS → DD Feature Shift | Accuracy62.4 | 28 | |
| Graph Reconstruction Attack | PROTEINS | Attack F162.1 | 25 | |
| Model Fingerprinting | PROTEINS | AUC97.1 | 24 | |
| Semi-supervised graph classification | PROTEINS (10-fold cross-validation) | Accuracy80.22 | 21 | |
| Graph Classification | PROTEINS 1.0 (test) | AUC0.89 | 17 | |
| Graph Classification | PROTEINS size shift (test) | MCC0.4 | 17 | |
| Federated Graph Classification | PROTEINS non-IID (test) | Average Gain5.12 | 16 | |
| Federated Graph Classification | PROTEINS (test) | Average Gain4.45 | 16 | |
| Graph Classification | PROTEINS TU (unsupervised) | Accuracy76.2 | 14 | |
| Graph-level classification | PROTEINS | MCC0.59 | 14 | |
| Graph Classification | PROTEINS TU (test) | Accuracy75.5 | 14 | |
| Graph-level Anomaly Detection | PROTEINS | AUPRC85.08 | 13 | |
| Graph Classification | Proteins | Certified Accuracy77.8 | 12 | |
| Watermark Verification | PROTEINS | Watermark Accuracy86 | 12 | |
| Ligand discovery | 100 Proteins Min Top-3 endpoint | MLT (Target PIC 7.0)13 | 11 | |
| Ligand discovery | 100 Proteins Average Top-10 endpoint | MLT Score (PIC 7.0)21 | 11 | |
| Anomaly Detection | PROTEINS | AUC (%)81.3 | 11 | |
| Graph Classification | PROTEINS 50-shot | AUROC66.78 | 11 |
Showing 25 of 65 rows