Drug Discovery On Bbbp
Métriques
AUC
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | AUC | Paper Title | Repository |
|---|---|---|---|
| ProtoW-L2 | 0.92 | Optimal Transport Graph Neural Networks | - |
| GIT-Mol(G+S) | 0.739 | GIT-Mol: A Multi-modal Large Language Model for Molecular Science with Graph, Image, and Text | - |
| ContextPred | 0.687 | Strategies for Pre-training Graph Neural Networks | - |
| elEmBERT-V1 | 0.905 | Structure to Property: Chemical Element Embeddings and a Deep Learning Approach for Accurate Prediction of Chemical Properties | - |
0 of 4 row(s) selected.