Drug Discovery On Sider
Metriken
AUC
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
| Paper Title | ||
|---|---|---|
| elEmBERT-V1 | 0.778 | Structure to Property: Chemical Element Embeddings and a Deep Learning Approach for Accurate Prediction of Chemical Properties |
| Ensemble locally constant networks | 0.685 | Oblique Decision Trees from Derivatives of ReLU Networks |
| GIT-Mol(G+S) | 0.634 | GIT-Mol: A Multi-modal Large Language Model for Molecular Science with Graph, Image, and Text |
| ContextPred | 0.627 | Strategies for Pre-training Graph Neural Networks |
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