Petri graph neural networks advance learning higher order multimodal complex interactions in graph structured data

Abstract Graphs are widely used to model interconnected systems, offering powerful tools for data representation and problem-solving. However, their reliance on pairwise, single-type, and static connections limits their expressive capacity. Recent developments extend this foundation through higher-o...

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Hlavní autoři:	Alma Ademovic Tahirovic, David Angeli, Adnan Tahirovic, Goran Strbac
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Nature Portfolio 2025-05-01
Edice:	Scientific Reports
Témata:	Heterogeneous network flow Higher-order complex networks Hypergraphs Multilayer networks Multimodal data Petri nets
On-line přístup:	https://doi.org/10.1038/s41598-025-01856-9
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