Graph Classification on MUV MoleculeNet random (train val test)
0.798ROC-AUCDuvenaud et al.
Evaluation Results
| Method | Links | |
|---|---|---|
| Duvenaud et al.Relational Pooling=false, Base Model (f)=Duvenaud et al. GNN2019.03 | 0.798 | |
| RP-DuvenaudRelational Pooling=true, Base Model (f)=Duvenaud et al. GNN2019.03 | 0.794 | |
| k-ary RP (k=20)Relational Pooling=true, k (subgraph size)=20, Base Model (f)=Duvenaud et al. GNN2019.03 | 0.777 | |
| k-ary RP (k=40)Relational Pooling=true, k (subgraph size)=40, Base Model (f)=Duvenaud et al. GNN2019.03 | 0.776 | |
| k-ary RP (k=30)Relational Pooling=true, k (subgraph size)=30, Base Model (f)=Duvenaud et al. GNN2019.03 | 0.776 | |
| k-ary RP (k=10)Relational Pooling=true, k (subgraph size)=10, Base Model (f)=Duvenaud et al. GNN2019.03 | 0.773 | |
| k-ary RP (k=50)Relational Pooling=true, k (subgraph size)=50, Base Model (f)=Duvenaud et al. GNN2019.03 | 0.768 | |
| RNN-DFSRelational Pooling=true, Base Model (f)=RNN, Orientation (DFS)=true2019.03 | 0.648 | |
| CNN-DFSRelational Pooling=true, Base Model (f)=CNN, Orientation (DFS)=true2019.03 | 0.601 |