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Published at November 9

Learning From Graph-Structured Data: Addressing Design Issues and Exploring Practical Applications in Graph Representation Learning

cs.LG

cs.AI

Released Date: November 9, 2024

Authors: Chenqing Hua

Arxiv: http://arxiv.org/abs/2411.07269v1

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DATASET	Cora	Citeseer	Pubmed
MODEL	Acc	Acc	Acc
GCN	0.8778 $\pm$ 0.0096	0.8139 $\pm$ 0.0123	0.8890 $\pm$ 0.0032
GAT	0.8686 $\pm$ 0.0042	0.6720 $\pm$ 0.0046	0.8328 $\pm$ 0.0012
GraphSAGE	0.8658 $\pm$ 0.0026	0.7624 $\pm$ 0.0030	0.8658 $\pm$ 0.0011
H₂GCN	0.8752 $\pm$ 0.0061	0.7997 $\pm$ 0.0069	0.8778 $\pm$ 0.0028
GPRGNN	0.7951 $\pm$ 0.0036	0.6763 $\pm$ 0.0038	0.8507 $\pm$ 0.0009
APPNP	0.7941 $\pm$ 0.0038	0.6859 $\pm$ 0.0030	0.8502 $\pm$ 0.0009
MixHop	0.6565 $\pm$ 0.1131	0.4952 $\pm$ 0.1335	0.8704 $\pm$ 0.0410
tGNN	0.8808 $\pm$ 0.0131	0.80.51 $\pm$ 0.0192	0.9080 $\pm$ 0.0018