Molecular property classification on HIV (scaffold)
0.789ROC AUCAPT
Evaluation results
| Method | Links | |
|---|---|---|
| APTBase Model=Mole-BERT2023.11 | 0.789 | |
| Mole-BERT2023.11 | 0.782 | |
| MAM2023.11 | 0.775 | |
| JOAO2023.11 | 0.769 | |
| GraphMAE2023.11 | 0.768 | |
| AD-GCL2023.11 | 0.767 | |
| APTBase Model=EdgePred2023.11 | 0.766 | |
| G-Contextual2023.11 | 0.763 | |
| EdgePred2023.11 | 0.763 | |
| MAMEncoder=vanilla VQ-VAE2023.11 | 0.762 | |
| GraphLoG2023.11 | 0.761 | |
| 3D InfoMax2023.11 | 0.761 | |
| GraphMVP2023.11 | 0.76 | |
| MGSSL2023.11 | 0.758 | |
| ContextPred2023.11 | 0.756 | |
| No pretrain2023.11 | 0.755 | |
| AttrMask2023.11 | 0.753 | |
| TMCL2023.11 | 0.753 | |
| GraphCL2023.11 | 0.751 | |
| SimGRACE2023.11 | 0.75 | |
| TMCLMode=w/o Ltri2023.11 | 0.746 | |
| InfoGraph2023.11 | 0.742 | |
| G-Motif2023.11 | 0.738 | |
| TMCLMode=w/o Lcon2023.11 | 0.735 | |
| GPT-GNN2023.11 | 0.652 |