Representing Graphs via Gromov-Wasserstein Factorization
Graph representation is a challenging and significant problem for many real-world applications. In this work, we propose a novel paradigm called "Gromov-Wasserstein Factorization" (GWF) to learn graph representations in a flexible and interpretable way. Given a set of graphs, whose corresp...
Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 45(2023), 1 vom: 23. Jan., Seite 999-1016 |
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Format: | Online-Aufsatz |
Sprache: | English |
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2023
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Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence |
Schlagworte: | Journal Article |
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