| graph-classification-on-dd | GATv2 | #40 | Accuracy: 75.966±2.191 |
| graph-classification-on-enzymes | GATv2 | #5 | Accuracy: 77.987±2.112 |
| graph-classification-on-imdb-b | GATv2 | #7 | Accuracy: 80.000±2.739 |
| graph-classification-on-nci1 | GATv2 | #27 | Accuracy: 82.384±1.700 |
| graph-classification-on-nci109 | GATv2 | #12 | Accuracy: 83.092±0.764 |
| graph-classification-on-proteins | GATv2 | #24 | Accuracy: 77.679±2.187 |
| graph-regression-on-esr2 | GATv2 | #6 | R2: 0.655±0.000RMSE: 0.518±0.655 |
| graph-regression-on-f2 | GATv2 | #6 | R2: 0.885±0.000RMSE: 0.344±0.885 |
| graph-regression-on-kit | GATv2 | #6 | R2: 0.826±0.000RMSE: 0.453±0.826 |
| graph-regression-on-lipophilicity | GATv2 | #2 | RMSE: 0.534±0.014R2: 0.821±0.009 |
| graph-regression-on-parp1 | GATv2 | #6 | R2: 0.919±0.000RMSE: 0.356±0.919 |
| graph-regression-on-pgr | GATv2 | #7 | R2: 0.666±0.000RMSE: 0.558±0.666 |
| graph-regression-on-zinc-full | GATv2 | #17 | Test MAE: 0.079±0.004 |
| molecular-property-prediction-on-esol | GATv2 | #7 | RMSE: 0.549±0.020R2: 0.928±0.005 |
| molecular-property-prediction-on-freesolv | GATv2 | #3 | RMSE: 0.676±0.081R2: 0.970±0.007 |
| node-property-prediction-on-ogbn-arxiv | GIANT+XRT+GATv2 | #17 | Test Accuracy: 0.7415 ± 0.0005Ext. data: Yes… |