OpenCodePapers

node-classification-on-amazon-photo-1

Node Classification
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PaperCodeAccuracyModelNameReleaseDate
Classic GNNs are Strong Baselines: Reassessing GNNs for Node Classification✓ Link96.78 ± 0.23GraphSAGE2024-06-13
Classic GNNs are Strong Baselines: Reassessing GNNs for Node Classification✓ Link96.60 ± 0.33GAT2024-06-13
Classic GNNs are Strong Baselines: Reassessing GNNs for Node Classification✓ Link96.10 ± 0.46GCN2024-06-13
Mixture of Experts Meets Decoupled Message Passing: Towards General and Adaptive Node Classification✓ Link95.81±0.41GNNMoE(GCN-like P)2024-12-11
Mixture of Experts Meets Decoupled Message Passing: Towards General and Adaptive Node Classification✓ Link95.71±0.37GNNMoE(GAT-like P)2024-12-11
Mixture of Experts Meets Decoupled Message Passing: Towards General and Adaptive Node Classification✓ Link95.46±0.24GNNMoE(SAGE-like P)2024-12-11
Inferring from References with Differences for Semi-Supervised Node Classification on Graphs✓ Link95.05%3ference2022-04-11
Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages✓ Link94.36%CoLinkDist2021-06-16
Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages✓ Link94.12%CoLinkDistMLP2021-06-16
Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages✓ Link93.83%LinkDistMLP2021-06-16
Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages✓ Link93.75%LinkDist2021-06-16
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