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Taming numerical imprecision by adapting the KL divergence to negative probabilities

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Umfang10 Seiten

Online
DOI: 10.48550/arXiv.2312.13021


Einrichtungen

  1. Lehr- und Forschungsgebiet Numerische Analysis (111620)
  2. Fachgruppe Mathematik (110000)


Inhaltliche Beschreibung (Schlagwörter)
Approximate Bayesian computation (frei) ; Kullback-Leibler divergence (frei) ; Mutual Hazard Networks (frei) ; Statistical optimization (frei) ; Tensor trains (frei)

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Dokumenttyp
Preprint

Format
online

Sprache
English

Externe Identnummern
arXiv: arXiv:2312.13021

Interne Identnummern
RWTH-2024-00354
Datensatz-ID: 976819

Beteiligte Länder
Germany, Switzerland

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Related:

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Journal Article  ;  ;  ;  ;  ;  ;
Taming numerical imprecision by adapting the KL divergence to negative probabilities
Statistics and computing 34(5), 168 () [10.1007/s11222-024-10480-y]  GO OpenAccess  Download fulltext Files BibTeX | EndNote: XML, Text | RIS

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Faculty of Mathematics and Natural Sciences (Fac.1) > Department of Mathematics
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111620
 Record created 2024-01-11, last modified 2025-11-13
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