TDC.PPBR_AZ Leaderboard
Dataset Summary
| Dataset | Unit | Size | Task | Metric | Dataset Split |
|---|---|---|---|---|---|
| TDC.PPBR_AZ | % | 1,797 | Regression | MAE | Scaffold |
Leaderboard
| Rank | Model | Contact | Link | #Params | MAE |
|---|---|---|---|---|---|
| 1 | Gradient Boost | Rob Learsch | GitHub, Paper | 1 | 7.440 ± 0.024 |
| 2 | MapLight + GNN | Jim Notwell | GitHub, Paper | N/A | 7.526 ± 0.106 |
| 3 | MapLight | Jim Notwell | GitHub, Paper | N/A | 7.660 ± 0.058 |
| 4 | MiniMol | Blazej Banaszewski | GitHub, Paper | N/A | 7.696 ± 0.125 |
| 5 | Chemprop | Kyle Swanson | GitHub, Paper | N/A | 7.788 ± 0.210 |
| 6 | BaseBoosting KyQVZ6b2 | David Huang | GitHub, Paper | N/A | 7.914 ± 0.096 |
| 7 | DeepMol (AutoML) | DeepMol team | GitHub, Paper | N/A | 7.990 ± 0.104 |
| 8 | ADMETrix | Rohit Singh Yadav | GitHub, Paper | N/A | 8.200 ± 0.114 |
| 9 | Chemprop-RDKit | Kyle Swanson | GitHub, Paper | N/A | 8.288 ± 0.173 |
| 10 | CFA | Nan Jiang | GitHub, Paper | N/A | 8.680 ± 0.262 |
| 11 | Basic ML | Nilavo Boral | GitHub, Paper | N/A | 9.185 ± 0.000 |
| 12 | NeuralFP | Kexin Huang | GitHub, Paper | 480,193 | 9.292 ± 0.384 |
| 13 | AttentiveFP | Kexin Huang | GitHub, Paper | 300,806 | 9.373 ± 0.335 |
| 14 | ContextPred | Kexin Huang | GitHub, Paper | 2,067,053 | 9.445 ± 0.224 |
| 15 | Euclia ML model | Euclia | GitHub, Paper | 50 | 9.942 ± 0.121 |
| 16 | RDKit2D + MLP (DeepPurpose) | Kexin Huang | GitHub, Paper | 633,409 | 9.994 ± 0.319 |
| 17 | AttrMasking | Kexin Huang | GitHub, Paper | 2,067,053 | 10.075 ± 0.202 |
| 18 | GCN | Kexin Huang | GitHub, Paper | 191,810 | 10.194 ± 0.373 |
| 19 | CNN (DeepPurpose) | Kexin Huang | GitHub, Paper | 226,625 | 11.106 ± 0.358 |
| 20 | Morgan + MLP (DeepPurpose) | Kexin Huang | GitHub, Paper | 1,477,185 | 12.848 ± 0.362 |
: The lower the better.