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HLSAD: Hodge Laplacian-based Simplicial Anomaly Detection
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2025
Person Schaub, Michael Thomas auch Corresponding author
Online
DOI: 10.48550/arXiv.2505.24534
DOI: 10.18154/RWTH-2025-05054
URL: https://publications.rwth-aachen.de/record/1012595/files/1012595.pdf
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Inhaltliche Beschreibung (Schlagwörter)
FOS: Computer and information sciences (Genormte SW) ; Machine Learning (cs.LG) (Genormte SW) ; Social and Information Networks (cs.SI) (Genormte SW)
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Dokumenttyp
Preprint
Format
online
Sprache
English
Externe Identnummern
arXiv: arXiv:2505.24534
Interne Identnummern
RWTH-2025-05054
Datensatz-ID: 1012595
Beteiligte Länder
Germany
Related:
Contribution to a book/Contribution to a conference proceedings
HLSAD: Hodge Laplacian-based Simplicial Anomaly Detection
KDD ’25 : Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2
31. ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2025, Toronto, ONToronto, ON, Canada, 3 Aug 2025 - 7 Aug 2025
New York, NY : Association for Computing Machinery 626-636 (2025) [10.1145/3711896.3736998]
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