Deep Constraint-Based Propagation in Graph Neural Networks

The popularity of deep learning techniques renewed the interest in neural architectures able to process complex structures that can be represented using graphs, inspired by Graph Neural Networks (GNNs). We focus our attention on the originally proposed GNN model of Scarselli et al. 2009, which encod...

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Bibliographische Detailangaben

Veröffentlicht in:	IEEE transactions on pattern analysis and machine intelligence. - 1979. - 44(2022), 2 vom: 15. Feb., Seite 727-739
1. Verfasser:	Tiezzi, Matteo (VerfasserIn)
Weitere Verfasser:	Marra, Giuseppe, Melacci, Stefano, Maggini, Marco
Format:	Online-Aufsatz
Sprache:	English
Veröffentlicht:	2022
Zugriff auf das übergeordnete Werk:	IEEE transactions on pattern analysis and machine intelligence
Schlagworte:	Journal Article Research Support, Non-U.S. Gov't