Node Classification on Amazon Photo

11개 결과 · ⬇ CSV · JSON

Accuracy

Rank	Model	Accuracy	Paper	Code	Year
1	GraphSAGE	96.78 ± 0.23	Classic GNNs are Strong Baselines: Reassessing GNNs for Node Classification	LUOyk1999/tunedGNN	2024
2	GAT	96.60 ± 0.33	Classic GNNs are Strong Baselines: Reassessing GNNs for Node Classification	LUOyk1999/tunedGNN	2024
3	GCN	96.10 ± 0.46	Classic GNNs are Strong Baselines: Reassessing GNNs for Node Classification	LUOyk1999/tunedGNN	2024
4	GNNMoE(GCN-like P)	95.81±0.41	Mixture of Experts Meets Decoupled Message Passing: Towards General and Adaptive Node Classification	GISec-Team/GNNMoE	2024
5	GNNMoE(GAT-like P)	95.71±0.37	Mixture of Experts Meets Decoupled Message Passing: Towards General and Adaptive Node Classification	GISec-Team/GNNMoE	2024
6	GNNMoE(SAGE-like P)	95.46±0.24	Mixture of Experts Meets Decoupled Message Passing: Towards General and Adaptive Node Classification	GISec-Team/GNNMoE	2024
7	3ference	95.05%	Inferring from References with Differences for Semi-Supervised Node Classification on Graphs	cf020031308/3ference	2022
8	CoLinkDist	94.36%	Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages	cf020031308/LinkDist · cf020031308/LinkDist	2021
9	CoLinkDistMLP	94.12%	Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages	cf020031308/LinkDist · cf020031308/LinkDist	2021
10	LinkDistMLP	93.83%	Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages	cf020031308/LinkDist · cf020031308/LinkDist	2021
11	LinkDist	93.75%	Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages	cf020031308/LinkDist · cf020031308/LinkDist	2021