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Learning Hybrid Dynamics Models with Simulator-Informed Latent States

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Umfang25 Seiten

Submitted on 6 Sep 2023 (v1), last revised 29 Jan 2024 (this version, v2)

Online
DOI: 10.48550/arXiv.2309.02873


Einrichtungen

  1. Lehrstuhl für Data Science im Maschinenbau (422610)
  2. Fachgruppe Informatik (120000)


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Dokumenttyp
Preprint

Format
online

Sprache
English

Externe Identnummern
arXiv: arXiv:2309.02873
OpenAlex: W4386556169

Interne Identnummern
RWTH-2024-02659
Datensatz-ID: 980964

Beteiligte Länder
Germany

 GO


Related:

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Contribution to a book/Contribution to a conference proceedings  ;  ;
Learning Hybrid Dynamics Models with Simulator-Informed Latent States
Thirty-Eighth AAAI Conference on Artificial Intelligence, Thirty-Sixth Conference on Innovative Applications of Artificial Intelligence, Fourteenth Symposium on Educational Advances in Artificial Intelligence / Edited by Michael Wooldridge, Jennifer Dy, Sriraam Natarajan ; Sponsored by the Association for the Advancement of Artificial Intelligence
38. Annual AAAI Conference on Artificial Intelligence, AAAI-24, VancouverVancouver, Canada, 20–27, 2024-02-20 - 27 Feb 202420–27, 2024-02-202024-02-27
Washington, DC : Association for the Advancement of Artificial Intelligence, Proceedings of the AAAI Conference on Artificial Intelligence 38,11 11892-11900 () [10.1609/aaai.v38i11.29075]  GO   Download fulltextHomepage of event BibTeX | EndNote: XML, Text | RIS


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Faculty of Mechanical Engineering (Fac.4)
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 Record created 2024-03-05, last modified 2026-08-31


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