Towards Stable, Globally Expressive Graph Representations with Laplacian Eigenvectors

Graph neural networks (GNNs) have achieved remarkable success in a variety of machine learning tasks over graph data. Existing GNNs usually rely on message passing, i.e., computing node representations by gathering information from the neighborhood, to build their underlying computational graphs. Th...

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Hauptverfasser:	Zhou, Junru, Zhou, Cai, Wang, Xiyuan, Li, Pan, Zhang, Muhan
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Learning
Online-Zugang:	Volltext bestellen
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