Node Classification on Coauthor Physics

14개 결과 · ⬇ CSV · JSON

Accuracy

Rank	Model	Accuracy	Paper	Code	Year
1	NCSAGE	98.69 ± 0.26	Clarify Confused Nodes via Separated Learning	GISec-Team/NCGNN	2023
2	NCGCN	98.63 ± 0.24	Clarify Confused Nodes via Separated Learning	GISec-Team/NCGNN	2023
3	GCN	97.46 ± 0.10	Classic GNNs are Strong Baselines: Reassessing GNNs for Node Classification	LUOyk1999/tunedGNN	2024
4	3ference	97.22%	Inferring from References with Differences for Semi-Supervised Node Classification on Graphs	cf020031308/3ference	2022
5	CoLinkDist	97.05%	Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages	cf020031308/LinkDist · cf020031308/LinkDist	2021
6	GNNMoE(GAT-like P)	97.05±0.19	Mixture of Experts Meets Decoupled Message Passing: Towards General and Adaptive Node Classification	GISec-Team/GNNMoE	2024
7	GNNMoE(GCN-like P)	97.03±0.13	Mixture of Experts Meets Decoupled Message Passing: Towards General and Adaptive Node Classification	GISec-Team/GNNMoE	2024
8	LinkDistMLP	96.91%	Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages	cf020031308/LinkDist · cf020031308/LinkDist	2021
9	Exphormer	96.89±0.09%	Exphormer: Sparse Transformers for Graphs	hamed1375/exphormer	2023
10	CoLinkDistMLP	96.87%	Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages	cf020031308/LinkDist · cf020031308/LinkDist	2021
10	LinkDist	96.87%	Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages	cf020031308/LinkDist · cf020031308/LinkDist	2021
12	GNNMoE(SAGE-like P)	96.81±0.22	Mixture of Experts Meets Decoupled Message Passing: Towards General and Adaptive Node Classification	GISec-Team/GNNMoE	2024
13	GraphMix (GCN)	94.49 ± 0.84	GraphMix: Improved Training of GNNs for Semi-Supervised Learning	vikasverma1077/GraphMix	2019
14	DAGNN (Ours)	94	Towards Deeper Graph Neural Networks	dmlc/dgl · mengliu1998/DeeperGNN · divelab/DeeperGNN	2020