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Author | Title | Accn# | Year | Item Type | Claims |
| 1 |
Bufano, Filomena |
Machine Learning for Astrophysics |
I12856 |
2023 |
eBook |
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| Title | Machine Learning for Astrophysics : Proceedings of the ML4Astro International Conference 30 May - 1 Jun 2022 |
| Author(s) | Bufano, Filomena;Riggi, Simone;Sciacca, Eva;Schilliro, Francesco |
| Publication | Cham, 1. Imprint: Springer
2. Springer International Publishing, 2023. |
| Description | XIV, 211 p. 52 illus., 47 illus. in color : online resource |
| Abstract Note | 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 |
| ISBN,Price | 9783031341670 |
| Keyword(s) | 1. ARTIFICIAL INTELLIGENCE
2. ASTRONOMY
3. Astronomy, Observations and Techniques
4. ASTROPHYSICS
5. EBOOK - SPRINGER
6. MACHINE LEARNING
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| Item Type | eBook |
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| I12856 |
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