Generalizing Graph Neural Networks on Out-of-Distribution Graphs
Graph Neural Networks (GNNs) are proposed without considering the agnostic distribution shifts between training graphs and testing graphs, inducing the degeneration of the generalization ability of GNNs in Out-Of-Distribution (OOD) settings. The fundamental reason for such degeneration is that most...
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Détails bibliographiques
| Publié dans: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 46(2024), 1 vom: 03. Jan., Seite 322-337
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| Auteur principal: |
Fan, Shaohua
(Auteur) |
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| Autres auteurs: |
Wang, Xiao,
Shi, Chuan,
Cui, Peng,
Wang, Bai |
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| Format: | Article en ligne
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| Langue: | English |
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| Publié: |
2024
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| Accès à la collection: | IEEE transactions on pattern analysis and machine intelligence
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| Sujets: | Journal Article |
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