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Machine Learning for Astrophysics Proceedings of the ML4Astro International Conference 30 May - 1 Jun 2022 /

This book reviews the state of the art in the exploitation of machine learning techniques for the astrophysics community and gives the reader a complete overview of the field. The contributed chapters allow the reader to easily digest the material through balanced theoretical and numerical methods a...

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Korporativní autor: SpringerLink (Online service)
Další autoři: Bufano, Filomena (Editor), Riggi, Simone (Editor), Sciacca, Eva (Editor), Schilliro, Francesco (Editor)
Médium: Elektronický zdroj E-kniha
Jazyk:angličtina
Vydáno: Cham : Springer International Publishing : Imprint: Springer, 2023.
Vydání:1st ed. 2023.
Edice:Astrophysics and Space Science Proceedings, 60
Témata:
Astrophysics.
Machine learning.
Artificial intelligence.
Astronomy > Observations.
Machine Learning.
Artificial Intelligence.
Astronomy, Observations and Techniques.
On-line přístup:https://doi.org/10.1007/978-3-031-34167-0
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Shrnutí:This book reviews the state of the art in the exploitation of machine learning techniques for the astrophysics community and gives the reader a complete overview of the field. The contributed chapters allow the reader to easily digest the material through balanced theoretical and numerical methods and tools with applications in different fields of theoretical and observational astronomy. The book helps the reader to really understand and quantify both the opportunities and limitations of using machine learning in several fields of astrophysics.
Fyzický popis:1 online resource (XIV, 211 p. 52 illus.). 47 illus. in color.
ISBN:9783031341670
ISSN:1570-6605 ;
DOI:10.1007/978-3-031-34167-0

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