Learning Graph Attentions via Replicator Dynamics
Graph Attention (GA) which aims to learn the attention coefficients for graph edges has achieved impressive performance in GNNs on many graph learning tasks. However, existing GAs are usually learned based on edges' (or connected nodes') features which fail to fully capture the rich struct...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - PP(2024) vom: 24. Apr.
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| 1. Verfasser: |
Jiang, Bo
(VerfasserIn) |
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| Weitere Verfasser: |
Zhang, Ziyan,
Ge, Sheng,
Wang, Beibei,
Wang, Xiao,
Tang, Jin |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2024
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence
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| Schlagworte: | Journal Article |
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