A Survey on Learning from Graphs with Heterophily: Recent Advances and Future Directions

Graphs are structured data that models complex relations between real-world entities. Heterophilic graphs, where linked nodes are prone to be with different labels or dissimilar features, have recently attracted significant attention and found many real-world applications. Meanwhile, increasing effo...

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Veröffentlicht in:	arXiv.org 2024-09
Hauptverfasser:	Gong, Chenghua, Cheng, Yao, Yu, Jianxiang, Xu, Can, Shan, Caihua, Luo, Siqiang, Li, Xiang
Format:	Artikel
Sprache:	eng
Schlagworte:	Graphs Learning Structured data Taxonomy
Online-Zugang:	Volltext
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