Molecular Property Prediction On Sider 1
Métriques
ROC-AUC
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | ROC-AUC |
|---|---|
| chemrl-gem-geometry-enhanced-molecular | 67.2 |
| galactica-a-large-language-model-for-science-1 | 55.9 |
| n-gram-graph-a-novel-molecule-representation | 65.5 |
| galactica-a-large-language-model-for-science-1 | 54.0 |
| uni-mol-a-universal-3d-molecular | 65.9 |
| molecular-structure-property-co-trained | 64.7 |
| grover-self-supervised-message-passing | 65.4 |
| bioact-het-a-heterogeneous-siamese-neural | 91.11 |
| integrating-convolutional-layers-and-biformer | 78.2 |
| molxpt-wrapping-molecules-with-text-for | 71.7 |
| are-learned-molecular-representations-ready | 57.0 |
| n-gram-graph-a-novel-molecule-representation | 66.8 |
| low-data-drug-discovery-with-one-shot | 70.40 |
| galactica-a-large-language-model-for-science-1 | 55.9 |
| pre-training-graph-neural-networks-on | 64.03±1.04 |
| pre-training-graph-neural-networks | 62.7 |
| galactica-a-large-language-model-for-science-1 | 63.2 |
| galactica-a-large-language-model-for-science-1 | 61.3 |
| grover-self-supervised-message-passing | 64.8 |