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Exploring hyper-parameter spaces of neuroscience models on high performance computers with Learning to Learn

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Umfang32 Seiten

Online
DOI: 10.18154/RWTH-2022-06684
DOI: 10.48550/ARXIV.2202.13822

URL: https://publications.rwth-aachen.de/record/849258/files/849258.pdf

Einrichtungen

  1. Lehr- und Forschungsgebiet Mathematik (114620)
  2. Fachgruppe Mathematik (110000)
  3. JARA-BRAIN (080010)
  4. JARA-Office (080005)
  5. Institut für Geometrie und Praktische Mathematik (111400)
  6. Neural Computation (124920)
  7. Fachgruppe Informatik (120000)


Inhaltliche Beschreibung (Schlagwörter)
connectivity generation (frei) ; high performance computing (frei) ; hyper-parameter optimization (frei) ; meta learning (frei) ; parameter exploration (frei) ; simulation (frei)

OpenAccess:
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External link:
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Dokumenttyp
Preprint

Format
online

Sprache
English

Externe Identnummern
arXiv: arXiv:2202.13822

Interne Identnummern
RWTH-2022-06684
Datensatz-ID: 849258

Beteiligte Länder
Germany

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Creative Commons Attribution CC BY 4.0 ; OpenAccess
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Faculty of Mathematics and Natural Sciences (Fac.1) > Department of Mathematics
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Faculty of Computer Science (Fac.9)
Central and Other Institutions
124920_20180911
Public records
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120000
080010
110000
114620
080005
111400
 Record created 2022-06-30, last modified 2024-10-25
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