Dataset not found. Browse the registry.
Molecular properties
Aqueous Solubility (AqSolDB)
AqSolDB collects experimental measurements of how readily compounds dissolve in water. The benchmark predicts logS from molecular fingerprints, with logS defined as the base-10 logarithm of solubility in moles per litre.
RegressionLicence: CC BY 4.0 via TDC; underlying source terms require verification before re-hostingTDC-AqSolDBTarget: Ytdc ↗
Loading model results…
At this operating point
Model comparison
p=10,000, n=100 · Lower RMSE is better
No scores at this operating point. Select another feature or sample budget.
Random Forest is marked with a diamond. Models are ordered by the selected metric.
Across sample budgets
Learning curves
All metric values at this operating point
| Model | RMSE | MAE | R² |
|---|---|---|---|
| TabPFN 3.5 | 2.086 | 1.648 | 0.1449 |
| GeneICL | 2.09 | 1.646 | 0.1516 |
| Random Forest | 2.098 | 1.626 | 0.1422 |
| Extra Trees | 2.099 | 1.628 | 0.1419 |
| LimiX2 | 2.103 | 1.646 | 0.08703 |
| TabM | 2.106 | 1.673 | 0.1247 |
| AutoGluon | 2.107 | 1.652 | 0.1294 |
| Random Forest (tuned) | 2.113 | 1.66 | 0.14 |
| RealTabPFN 2.5 | 2.119 | 1.656 | 0.1172 |
| Kumo Tabular (M) | 2.126 | 1.666 | 0.08367 |
| RealTabPFN v2 | 2.134 | 1.694 | 0.1132 |
| MLP | 2.148 | 1.7 | 0.07983 |
| MLP (tuned) | 2.159 | 1.709 | 0.06368 |
| Logistic Regression | 2.168 | 1.689 | 0.08293 |
| MITRA | 2.172 | 1.703 | 0.05265 |
| Extra Trees (tuned) | 2.188 | 1.71 | 0.06137 |
| XGBoost (tuned) | 2.198 | 1.721 | 0.05131 |
| XGBoost | 2.203 | 1.725 | 0.03555 |
| Logistic Regression (tuned) | 2.204 | 1.728 | 0.05816 |
| RealMLP | 2.263 | 1.753 | 0.002899 |
| TabFM | 2.264 | 1.788 | -0.07479 |
| TabDPT | 2.272 | 1.76 | 0.01669 |
| Causilo | 2.286 | 1.814 | -0.0856 |