Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting

While Graph Neural Networks (GNNs) have achieved remarkable results in a variety of applications, recent studies exposed important shortcomings in their ability to capture the structure of the underlying graph. It has been shown that the expressive power of standard GNNs is bounded by the Weisfeiler...

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Veröffentlicht in:	IEEE transactions on pattern analysis and machine intelligence. - 1979. - 45(2023), 1 vom: 24. Jan., Seite 657-668
1. Verfasser:	Bouritsas, Giorgos (VerfasserIn)
Weitere Verfasser:	Frasca, Fabrizio, Zafeiriou, Stefanos, Bronstein, Michael M
Format:	Online-Aufsatz
Sprache:	English
Veröffentlicht:	2023
Zugriff auf das übergeordnete Werk:	IEEE transactions on pattern analysis and machine intelligence
Schlagworte:	Journal Article