Topological signal processing and learning: Recent advances and future challenges

Developing methods to process irregularly structured data is crucial in applications like gene-regulatory, brain, power, and socioeconomic networks. Graphs have been the go-to algebraic tool for modeling the structure via nodes and edges capturing their interactions, leading to the establishment of...

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Veröffentlicht in:	Signal processing Jg. 233; S. 109930
Hauptverfasser:	Isufi, Elvin, Leus, Geert, Beferull-Lozano, Baltasar, Barbarossa, Sergio, Di Lorenzo, Paolo
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.08.2025
Schlagworte:	Graph machine learning Graph signal processing Hodge theory Network science Topological data analysis Topological deep learning Topological signal processing Graph machine learning Topological signal processing Hodge theory Topological data analysis Graph signal processing Network science Topological deep learning
ISSN:	0165-1684
Online-Zugang:	Volltext
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