| ExpC | No | 1369397 | 0.7976 ± 0.0072 | 0.7518 ± 0.0080 | Breaking the Expressive Bottlenecks of Graph Neural Networks | |
| GCN | No | 479437 | 0.6839 ± 0.0084 | 0.6497 ± 0.0034 | Semi-Supervised Classification with Graph Convolutional Networks | |
| DeeperGCN | No | 2336421 | 0.7712 ± 0.0071 | 0.7313 ± 0.0078 | DeeperGCN: All You Need to Train Deeper GCNs | |
| GIN+virtual node | No | 3288042 | 0.7037 ± 0.0107 | 0.6678 ± 0.0105 | How Powerful are Graph Neural Networks? | |
| DeeperGCN+FLAG | No | 2336421 | 0.7752 ± 0.0069 | 0.7484 ± 0.0052 | Robust Optimization as Data Augmentation for Large-scale Graphs | |
| GIN+FLAG | No | 1836942 | 0.6905 ± 0.0092 | 0.6465 ± 0.0070 | Robust Optimization as Data Augmentation for Large-scale Graphs | |
| GCN+virtual node+FLAG | No | 1930537 | 0.6944 ± 0.0052 | 0.6638 ± 0.0055 | Robust Optimization as Data Augmentation for Large-scale Graphs | |
| GIN+virtual node+FLAG | No | 3288042 | 0.7245 ± 0.0114 | 0.6789 ± 0.0079 | Robust Optimization as Data Augmentation for Large-scale Graphs | |
| GIN | No | 1836942 | 0.6892 ± 0.0100 | 0.6562 ± 0.0107 | How Powerful are Graph Neural Networks? | |
| GCN+virtual node | No | 1930537 | 0.6857 ± 0.0061 | 0.6511 ± 0.0048 | Semi-Supervised Classification with Graph Convolutional Networks | |
| GPS | No | 3434533 | 0.8015 | 0.7556 ± 0.0027 | Recipe for a General, Powerful, Scalable Graph Transformer | |