Learning Dynamic Graph Embeddings with Neural Controlled Differential Equations

This paper focuses on representation learning for dynamic graphs with temporal interactions. A fundamental issue is that both the graph structure and the nodes own their own dynamics, and their blending induces intractable complexity in the temporal evolution over graphs. Drawing inspiration from th...

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Publié dans:	IEEE transactions on pattern analysis and machine intelligence. - 1979. - PP(2025) vom: 03. Okt.
Auteur principal:	Qin, Tiexin (Auteur)
Autres auteurs:	Walker, Benjamin, Lyons, Terry, Yan, Hong, Li, Haoliang
Format:	Article en ligne
Langue:	English
Publié:	2025
Accès à la collection:	IEEE transactions on pattern analysis and machine intelligence
Sujets:	Journal Article