Node Classification on ogbn-products transductive OGB (test)
87.36AccuracyGLEM
Evaluation Results
| Method | Links | |||
|---|---|---|---|---|
| GLEMGNN Backbone=SAGN+SCR2023.08 | 87.36 | — | — | |
| X-GIANTGNN Backbone=SAGN+SCR2023.08 | 86.12 | — | — | |
| X-SimTeGGNN Backbone=SAGN+SCR2023.08 | 85.4 | — | — | |
| X-SimTeGGNN Backbone=GraphSAGE2023.08 | 84.59 | — | 0.81 | |
| GLEMGNN Backbone=GraphSAGE2023.08 | 83.16 | — | 4.2 | |
| X-GIANTGNN Backbone=GraphSAGE2023.08 | 82.84 | — | 3.28 | |
| X-OGBGNN Backbone=SAGN+SCR2023.08 | 81.82 | — | — | |
| X-OGBGNN Backbone=GraphSAGE2023.08 | 78.81 | — | 3.01 | |
| SAGE2021.10 | 78.61 | — | — | |
| GLNN+width_factor=w82021.10 | 77.65 | 13.14 | -0.97 | |
| X-GIANTGNN Backbone=MLP2023.08 | 77.58 | 8.54 | — | |
| X-SimTeGGNN Backbone=MLP2023.08 | 76.73 | 8.67 | — | |
| MLP+width_factor=w82021.10 | 64.5 | — | — | |
| X-OGBGNN Backbone=MLP2023.08 | 50.86 | 30.96 | — |