Drug Discovery On Toxcast
Metriken
AUC
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Modellname | AUC | Paper Title | Repository |
|---|---|---|---|
| TrimNet | 0.777 | TrimNet: learning molecular representation from triplet messages for biomedicine | |
| GraphConv | 0.754 | Convolutional Networks on Graphs for Learning Molecular Fingerprints | |
| GraphConv + dummy super node | 0.768 | Learning Graph-Level Representation for Drug Discovery | |
| GIT-Mol(G+S) | 0.668 | GIT-Mol: A Multi-modal Large Language Model for Molecular Science with Graph, Image, and Text | |
| ContextPred | 0.657 | Strategies for Pre-training Graph Neural Networks | - |
0 of 5 row(s) selected.