Graph Regression on OGB-LSC PCQM4M v2 (test-dev)
0.0872MAEEGT-Large (24 layers)
Evaluation Results
| Method | Links | |
|---|---|---|
| EGT-Large (24 layers)#Param=89.3M, Layers=242021.08 | 0.0872 | |
| EGT# Param.=89.3M2022.05 | 0.0872 | |
| GRPE# Param.=46.2M2022.05 | 0.0898 | |
| GIN-VN#Param=6.7M2021.08 | 0.1084 | |
| GIN-virtual# Param.=6.7M2022.05 | 0.1084 | |
| GCN-VN#Param=4.9M2021.08 | 0.1152 | |
| GCN-virtual# Param.=4.9M2022.05 | 0.1152 | |
| GIN#Param=3.8M2021.08 | 0.1218 | |
| GIN# Param.=3.8M2022.05 | 0.1218 | |
| GCN#Param=2.0M2021.08 | 0.1398 | |
| GCN# Param.=2.0M2022.05 | 0.1398 |