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ResearchFormerly WizWand

Accuracy on Cora (Node classification)

89.46AccuracyBES
69.117674.398879.6884.9612Aug 24, 2024Dec 12, 2024Apr 2, 2025Jul 21, 2025Nov 9, 2025Feb 27, 2026Jun 18, 2026
Updated 4mo ago

Evaluation results

MethodLinks
BES2026.0689.46
GraphECL2026.0688.72
GCN2026.0588.7
SAGEConv2026.0588.7
H2GCN2026.0688.69
IGCL2026.0688.6
HGNN2026.0588.5
SGC2026.0588.4
SGC2026.0688.29
fCWN2026.0588.1
SSGC2026.0687.86
GCN2026.0687.74
GraphSAGE2026.0687.74
SGNN2026.0687.74
MotifRGC-GCNBackbone=GCN2026.0687.73
MotifRGC-GATBackbone=GAT2026.0687.62
MotifRGC-SAGEBackbone=GraphSAGE2026.0687.54
GAT2026.0587.5
KGNN2026.0687.49
Cheb2026.0687.31
sCWNc2026.0587.3
GAT2026.0687.18
GATv22026.0686.32
GIN2026.0586.2
MPNN-SAGEBackbone=GraphSAGE2026.0686.2
MPNN-GATBackbone=GAT2026.0686.14
MPNN-GCNBackbone=GCN2026.0685.52
DiGGR2024.0884.96
GiGaMAE2024.0884.72
Bandana2024.0884.62
GraphMAE22024.0884.5
GraphMAEMethod Category=Feature-based2024.1084.5
lrGAE 8Method Category=Structure-based2024.1084.5
MaskGAEMethod Category=Structure-based2024.1084.4
VEPM2024.0884.3
SEEGERA2024.0884.3
CCA-SSG2024.0884.2
GraphMAE2024.0884.2
lrGAE 7Method Category=Structure-based2024.1084.2
IPGDN2024.0884.1
SFABT2024.0884.1
S2GAEMethod Category=Structure-based2024.1084.1
SeeGeraMethod Category=Feature-based2024.1084
lrGAE 6Method Category=Structure-based2024.1084
AUG-MAEMethod Category=Feature-based2024.1083.9
DisenGCN2024.0883.7
S3GCLMethod Category=Standard GCL2024.1083.7
GraphMAE2Method Category=Feature-based2024.1083.7
EPAGCLMethod Category=Standard GCL2024.1083.6
MVGRL2024.0883.5
InfoGCL2024.0883.5
CCA-SSGMethod Category=Standard GCL2024.1083.5
MA-GCL2024.0883.3
GGDMethod Category=Standard GCL2024.1083.2
GiGaMAEMethod Category=Feature-based2024.1083.2
GAT2024.0883
GRACEMethod Category=Standard GCL2024.1082.9
BGRLMethod Category=Standard GCL2024.1082.8
BGRL2024.0882.7
DGI2024.0882.3
DGIMethod Category=Standard GCL2024.1082.3
NodeImport-GCNBackbone=GCN2026.0682.14
GRACE2024.0881.9
GCN2024.0881.5
SheafHyperGNN2026.0581.3
SheafHyperGNNArchitecture Tier=Native Tier (set-function / message passing), Hidden dimension=64, Training Recipe=architecture-specific recipes2026.0581.3
NodeImport-GATBackbone=GAT2026.0681.18
CWN2026.0581.1
RADE-OFBackbone=GCN2026.0581.08
RADE-OFSBackbone=GCN2026.0580.82
DropNodeBackbone=GCN2026.0580.8
DropoutBackbone=GCN2026.0580.76
DropMessageBackbone=GCN2026.0580.65
ED-HNN2026.0580.3
ED-HNNArchitecture Tier=Native Tier (set-function / message passing), Hidden dimension=64, Training Recipe=architecture-specific recipes2026.0580.3
DropEdgeBackbone=GCN2026.0580.28
GCNBackbone=GCN2026.0580.1
NodeImport-SAGEBackbone=GraphSAGE2026.0679.96
GAEMethod Category=Structure-based2024.1079.8
SERBackbone=GT, Regularization Strategy=Structure Entropy Regularization2026.0578.96
LapRBackbone=GT, Regularization Strategy=Laplacian Regularization2026.0578.69
R-regBackbone=GT, Regularization Strategy=R-reg2026.0578.57
DENSNET-D2026.0577.5
DENSNET-DArchitecture Tier=Density-Aware Tier (ours), Hidden dimension=128, Training Recipe=shared ANCS recipe2026.0577.5
CPBackbone=GT, Regularization Strategy=Canonical Polyadic2026.0577.43
UniGNN2026.0577.3
UniGNNArchitecture Tier=Native Tier (set-function / message passing), Hidden dimension=64, Training Recipe=shared ANCS recipe2026.0577.3
VanillaBackbone=GT, Regularization Strategy=None2026.0576.6
VGAE2024.0876.3
AllDeepSets2026.0576.2
AllDeepSetsArchitecture Tier=Native Tier (set-function / message passing), Hidden dimension=64, Training Recipe=shared ANCS recipe2026.0576.2
P-regBackbone=GT, Regularization Strategy=P-reg2026.0575.8
MLP2026.0574.1
MLPArchitecture Tier=Feature-only reference, Hidden dimension=64, Training Recipe=shared ANCS recipe2026.0574.1
HNHN2026.0572.8
HNHNArchitecture Tier=Native Tier (set-function / message passing), Hidden dimension=64, Training Recipe=shared ANCS recipe2026.0572.8
GAE2024.0871.5
HyperGCN2026.0571
HyperGCNArchitecture Tier=CE Tier (clique expansion), Hidden dimension=64, Training Recipe=shared ANCS recipe2026.0571
HGNN2026.0569.9