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ResearchFormerly WizWand

Graph Classification on MolHIV

87.4ROC AUCOur Method
58.217665.793873.3780.9462Oct 7, 2021Jul 22, 2022May 6, 2023Feb 18, 2024Dec 2, 2024Sep 16, 2025Jul 2, 2026
Updated 4mo ago

Evaluation results

MethodLinks
Our Method2026.0387.4
FragNet2026.0381.32
CIN2021.1080.94
Cluster-GTruns=4, seeds=42024.1080.93
Graphormer2026.0380.51
CCINRuns=9, Seed=1-92026.0580.45
Graph MLP-Mixerruns=4, seeds=42024.1079.97
Graph-ViT-MLPMixer2026.0379.97
tGNNedge features=none2022.0579.9
DGN2021.1079.7
DGNedge features=none2022.0579.7
GNN-AK+backbone=GIN2021.1079.61
GNN-AK+backbone=GCN2021.1079.28
PHM-GNNedge features=none2022.0579.1
PNA2021.1079.05
PNA*2021.1079.05
G3NRuns=9, Seed=1-92026.0579
GIN + GRANOLABackbone=GIN, Normalization=GRANOLA, RNF-Adaptive=true2024.0478.98
Trans. with X-LogSMaskvariant=ours2026.0778.91
GIN2021.1078.81
HIMP2021.1078.8
GNN-AK+backbone=PNA*2021.1078.8
GPSruns=4, seeds=42024.1078.8
GraphGPS2026.0778.8
HTMLRuns=9, Seed=1-92026.0578.68
CWNRuns=9, Seed=1-92026.0578.58
GraphSNNRuns=9, Seed=1-92026.0578.51
WLHNRuns=9, Seed=1-92026.0578.41
GNN-AKbackbone=GIN2021.1078.29
GNN-AK+backbone=GCN, Sampling=SubgraphDrop2021.1078.25
MSPNRuns=9, Seed=1-92026.0578.25
GNN-AK+backbone=GIN, Sampling=SubgraphDrop2021.1078.22
GNN-AK+backbone=PNA*, Sampling=SubgraphDrop2021.1078.21
GIN + GraphNormBackbone=GIN, Normalization=GraphNorm2024.0478.08
GSN2021.1077.99
GSNRuns=9, Seed=1-92026.0577.99
Graph ViTruns=4, seeds=42024.1077.92
SAN2026.0777.85
SAN+LapPEruns=4, seeds=42024.1077.75
Trans. with X-LogSMasklayers=1-layer2026.0777.68
DA-MoE2025.1177.62
GIN + RNF-NORMBackbone=GIN, Normalization=RNF-NORM2024.0477.61
SAGMM2025.1177.48
GMoE-GCN2025.1177.35
GIN + GRANOLA-NO-RNFBackbone=GIN, Normalization=GRANOLA, RNF-Adaptive=false2024.0477.09
GINRuns=9, Seed=1-92026.0577.07
GIN2026.0777.07
BNPool2025.1277
GIN + InstanceNormBackbone=GIN, Normalization=InstanceNorm2024.0476.88
GIN + SuperNormBackbone=GIN, Normalization=SuperNorm2024.0476.55
GIN + MeanSubtractionNormBackbone=GIN, Normalization=MeanSubtractionNorm2024.0476.37
GraphTrans2026.0776.33
GIN + PairNormBackbone=GIN, Normalization=PairNorm2024.0476.18
GIN + LayerNorm-graphBackbone=GIN, Normalization=LayerNorm-graph2024.0476.13
GCNedge features=none2022.0576.1
GCN2025.1176.06
ASAP2025.1276
Top-k2025.1276
k-MIS2025.1276
HOSC2025.1276
GCN2026.0775.99
GIN + BatchNorm + RNF-PEBackbone=GIN, Normalization=BatchNorm, Positional Encoding=RNF-PE2024.0475.98
HGCNRuns=9, Seed=1-92026.0575.91
GINedge features=none2022.0575.6
GIN + BatchNormBackbone=GIN, Normalization=BatchNorm2024.0475.58
GraphSAGE2025.1175.54
GIN + NodeNormBackbone=GIN, Normalization=NodeNorm2024.0475.5
GIN + GraphSizeNormBackbone=GIN, Normalization=GraphSizeNorm2024.0475.44
GIN2025.1175.4
GIN + LayerNorm-nodeBackbone=GIN, Normalization=LayerNorm-node2024.0475.24
ECPool2025.1275
MinCut2025.1275
ACC2025.1275
NDP2025.1275
DMoN2025.1275
Graphormer2026.0774.55
ALL-INTraining Scope=Trained on all datasets, Node Properties=Standard2026.0574.49
GIN + DiffGroupNormBackbone=GIN, Normalization=DiffGroupNorm2024.0474.37
GCN2021.1074.22
GraClus2025.1274
LaPool2025.1274
Diffpool2025.1274
ALL-IN-SPECIALIZEDTraining Scope=Trained per dataset, Node Properties=Standard2026.0573.78
GAT2025.1173.4
JBPool2025.1273
ALL-INTraining Scope=Trained on all datasets, Node Properties=0 props2026.0572.74
ALL-IN-SPECIALIZEDTraining Scope=Trained per dataset, Node Properties=0 props2026.0572.65
HANreproduced=official implementation2026.0372.3
SAG2025.1272
GIN + IdentityBackbone=GIN, Normalization=None2024.0471.89
PAN2025.1271
ChebNetreproduced=official implementation2026.0370.1
MaxCut2025.1270
AIAType=Graph Augmentation2022.1161.64
GREAType=Graph Augmentation2022.1160.71
OOD-GNNType=Graph Generalization2022.1160.6
FLAGType=Graph Augmentation2022.1160.59
ERMType=General Generalization2022.1159.94
CIGAType=Graph Generalization2022.1159.55
G-MixupType=Graph Augmentation2022.1159.34