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ResearchFormerly WizWand

Node Classification on Yelp (accuracy)

93.4AccuracyCoE
15.857635.988856.1276.2512May 27, 2025Jul 24, 2025Sep 20, 2025Nov 17, 2025Jan 14, 2026Mar 13, 2026May 11, 2026
Updated 5mo ago

Evaluation results

MethodLinks
CoEBackbone=GCN, Learning Paradigm=Proposed Graph-MoE2025.0593.4
InfoMGFBackbone=GCN, Learning Paradigm=Unsupervised multiplex2025.0592.01
GMoEBackbone=GCN, Learning Paradigm=Graph-MoE2025.0591.92
MowstBackbone=GCN, Learning Paradigm=Graph-MoE2025.0591.31
SUBLIMEBackbone=GCN, Learning Paradigm=Unsupervised GSL2025.0590.91
NodeFormerBackbone=GCN, Learning Paradigm=Supervised GSL2025.0590.76
STABLEBackbone=GCN, Learning Paradigm=Unsupervised GSL2025.0589.77
IDGLBackbone=GCN, Learning Paradigm=Supervised GSL2025.0588.28
LDSBackbone=GCN, Learning Paradigm=Supervised GSL2025.0587.11
GSRBackbone=GCN, Learning Paradigm=Unsupervised GSL2025.0584.46
GRCNBackbone=GCN, Learning Paradigm=Supervised GSL2025.0578.3
GCNBackbone=GCN, Learning Paradigm=Supervised structure-fixed GNN2025.0574.03
HDMIBackbone=GCN, Learning Paradigm=Unsupervised multiplex2025.0573.75
GENBackbone=GCN, Learning Paradigm=Supervised GSL2025.0569.22
ProGNNBackbone=GCN, Learning Paradigm=Supervised GSL2025.0560.43
HANBackbone=GCN, Learning Paradigm=Supervised structure-fixed GNN2025.0552.04
Whole DatasetRatio (r)=100%2026.0533.71
AHGCDDRatio (r)=0.5%2026.0527.09
AHGCDDRatio (r)=0.25%2026.0526.8
AHGCDD-XRatio (r)=0.5%2026.0526.19
HGCPARatio (r)=0.5%2026.0525.93
AHGCDDRatio (r)=0.05%2026.0525.43
RandomRatio (r)=0.5%2026.0525.27
AHGCDD-XRatio (r)=0.25%2026.0524.64
HerdingRatio (r)=0.5%2026.0523.83
HGCPARatio (r)=0.25%2026.0523.75
AHGCDD-XRatio (r)=0.05%2026.0523.67
HerdingRatio (r)=0.25%2026.0523.01
RandomRatio (r)=0.25%2026.0522.79
HGCPARatio (r)=0.05%2026.0522.6
K-CenterRatio (r)=0.5%2026.0522.53
RandomRatio (r)=0.05%2026.0521.82
HerdingRatio (r)=0.05%2026.0521.78
K-CenterRatio (r)=0.25%2026.0521.78
K-CenterRatio (r)=0.05%2026.0518.84