Graph Classification on IMDB-B
86.8AccuracyESA
Evaluation Results
| Method | Links | |
|---|---|---|
| ESA2024.02 | 86.8 | |
| GAT2024.02 | 84.2 | |
| AutoGELType=AutoGNN2021.12 | 81.2 | |
| DropGIN2024.02 | 80.4 | |
| GCN2024.02 | 80.2 | |
| TokenGT2024.02 | 80.2 | |
| GATv22024.02 | 80 | |
| GPS2024.02 | 79.4 | |
| GraphCrocEpochs=1002024.10 | 78.75 | |
| ProtGNN2026.05 | 78.3 | |
| ProtGNN2026.05 | 78.3 | |
| PNA2024.02 | 78 | |
| Graphormer2024.02 | 78 | |
| (s)GIN-0neighborhood enlargement=true, epsilon=02019.05 | 77.94 | |
| GraphGPS2026.07 | 77.4 | |
| PXGL-GNN2025.12 | 77.35 | |
| SEG-BERT*Strategy=Best results obtained with all three unification strategies2020.02 | 77.2 | |
| UGformerArchitecture=Variant 1, Inference Setting=Inductive, Evaluation Protocol=10-fold cross-validation2019.09 | 77.04 | |
| UGT# Parameters=55,5082023.11 | 77.04 | |
| UGT2023.11 | 77.04 | |
| Trans. with X-LogSMaskvariant=ours2026.07 | 77 | |
| GNTK2019.05 | 76.9 | |
| GIC2018.11 | 76.7 | |
| GraphMAE2 + COREmasking process=GraphMAE22025.12 | 76.7 | |
| GraphCrocEpochs=102024.10 | 76.69 | |
| GIN2024.02 | 76.6 | |
| RADE-OFSBackbone=GCN2026.05 | 76.6 | |
| DDMProtocol=Unsupervised representation learning2023.06 | 76.4 | |
| CTQWformer2026.05 | 76.4 | |
| RADE-OFBackbone=GAT2026.05 | 76.3 | |
| δ-3-LWL+Type=Local Kernel2019.04 | 76.2 | |
| GraphMAE22025.12 | 76.2 | |
| DropNodeBackbone=GCN2026.05 | 76.2 | |
| RADE-OFBackbone=GCN2026.05 | 76.2 | |
| RADE-OFSBackbone=GAT2026.05 | 76.2 | |
| (s)GCNneighborhood enlargement=true2019.05 | 76.1 | |
| GraphMAE + COREmasking process=GraphMAE2025.12 | 76.1 | |
| DropNodeBackbone=GAT2026.05 | 76.1 | |
| Trans. with X-LogSMasklayers=1-layer2026.07 | 76 | |
| SAT2026.07 | 75.9 | |
| GCMAE2025.12 | 75.8 | |
| DropoutBackbone=GCN2026.05 | 75.8 | |
| S2GAE2025.12 | 75.77 | |
| S2GAE2024.10 | 75.76 | |
| S2GAEPre-training Type=Generative2023.09 | 75.76 | |
| δ-2-LWL+Type=Local Kernel2019.04 | 75.7 | |
| GCNBackbone=GCN2026.05 | 75.7 | |
| DropEdgeBackbone=GCN2026.05 | 75.7 | |
| PDF2023.05 | 75.6 | |
| AUG-MAE2025.12 | 75.6 | |
| GraphMAEProtocol=Unsupervised representation learning2023.06 | 75.52 | |
| GraphMAE2024.10 | 75.52 | |
| StructMAE2024.10 | 75.52 | |
| GraphMAEPre-training Type=Generative2023.09 | 75.52 | |
| GraphMAEEvaluation protocol=Unsupervised representation learning2024.05 | 75.5 | |
| GraphMAE2025.12 | 75.5 | |
| DropMessageBackbone=GAT2026.05 | 75.5 | |
| SEG-BERTStrategy=padding/pruning, Graph residual terms=none2020.02 | 75.4 | |
| DropMessageBackbone=GCN2026.05 | 75.4 | |
| SAN2025.12 | 75.27 | |
| (s)GIN-epsilonneighborhood enlargement=true2019.05 | 75.19 | |
| GIN2019.04 | 75.1 | |
| WKPI-KC2019.04 | 75.1 | |
| GIN-0neighborhood enlargement=false, epsilon=02019.05 | 75.1 | |
| GIN2019.05 | 75.1 | |
| GIN-0Learning paradigm=Supervised Approaches2021.10 | 75.1 | |
| InfoGCLLearning paradigm=Unsupervised Approaches2021.10 | 75.1 | |
| GINType=Manual GNNs2021.12 | 75.1 | |
| GIN-0Inference Setting=Inductive, Evaluation Protocol=10-fold cross-validation2019.09 | 75.1 | |
| GIN2023.05 | 75.1 | |
| GINProtocol=Unsupervised representation learning2023.06 | 75.1 | |
| InfoGCL2024.10 | 75.1 | |
| GIN2025.12 | 75.1 | |
| InfoGCL2025.12 | 75.1 | |
| GIN2026.07 | 75.1 | |
| CDLLabel=50%2024.11 | 74.9 | |
| CDLLabel=70%2024.11 | 74.9 | |
| GCN22023.05 | 74.8 | |
| StructPoolevaluation_protocol=10-fold cross-validation2021.07 | 74.7 | |
| SEG-BERTStrategy=padding/pruning, Graph residual terms=raw2020.02 | 74.7 | |
| GAT2026.07 | 74.7 | |
| CDLLabel=30%2024.11 | 74.6 | |
| DropEdgeBackbone=GAT2026.05 | 74.6 | |
| SAGNN2025.12 | 74.53 | |
| LTP2023.05 | 74.5 | |
| GLIALabel=70%2024.11 | 74.5 | |
| GraphTrans2026.07 | 74.5 | |
| AWEAlgorithm Grouping=DD2018.05 | 74.45 | |
| AWE2020.02 | 74.45 | |
| AWE2019.05 | 74.45 | |
| AWE2023.05 | 74.45 | |
| WWL2019.06 | 74.37 | |
| GIN-epsilonneighborhood enlargement=false2019.05 | 74.3 | |
| GIN-eLearning paradigm=Supervised Approaches2021.10 | 74.3 | |
| GLIALabel=50%2024.11 | 74.3 | |
| DropMessageBackbone=GIN2026.05 | 74.3 | |
| DropoutBackbone=GAT2026.05 | 74.3 | |
| GCN2026.07 | 74.3 | |
| AIA2022.11 | 74.23 | |
| mvgrlLearning paradigm=Unsupervised Approaches2021.10 | 74.2 |