From Local Structures to Size Generalization in Graph Neural Networks

Graph neural networks (GNNs) can process graphs of different sizes, but their ability to generalize across sizes, specifically from small to large graphs, is still not well understood. In this paper, we identify an important type of data where generalization from small to large graphs is challenging...

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Hauptverfasser:	Yehudai, Gilad, Fetaya, Ethan, Meirom, Eli, Chechik, Gal, Maron, Haggai
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Learning Computer Science - Neural and Evolutionary Computing Statistics - Machine Learning
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