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HLSAD: Hodge Laplacian-based Simplicial Anomaly Detection

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In
KDD ’25 : Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2, Seiten/Artikel-Nr: 626-636

Konferenz/Event:31. ACM SIGKDD Conference on Knowledge Discovery and Data Mining , Toronto, ON , Canada , KDD 2025 , 2025-08-03 - 2025-08-07

ImpressumNew York, NY : Association for Computing Machinery

Umfang626-636

ISBN979-8-4007-1454-2, 9798400714542

Online
DOI: 10.1145/3711896.3736998

DOI: 10.18154/RWTH-2025-08011
URL: https://publications.rwth-aachen.de/record/1018835/files/1018835.pdf

Einrichtungen

  1. Juniorprofessur für Computational Network Science (125230)
  2. Fachgruppe Informatik (120000)


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Dokumenttyp
Contribution to a book/Contribution to a conference proceedings

Format
online

Sprache
English

Anmerkung
Peer review status of article unknown

Externe Identnummern
SCOPUS: SCOPUS:2-s2.0-105014313930

Interne Identnummern
RWTH-2025-08011
Datensatz-ID: 1018835

Beteiligte Länder
Germany

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Related:

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Preprint  ;
HLSAD: Hodge Laplacian-based Simplicial Anomaly Detection
11 Seiten () [10.48550/arXiv.2505.24534]  GO OpenAccess  Download fulltext Files  Download fulltextFulltext by arXiv.org BibTeX | EndNote: XML, Text | RIS

Creative Commons Attribution CC BY 4.0 ; OpenAccess
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 Record created 2025-09-23, last modified 2025-09-29
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