Machine Learning for Astrophysics: Proceedings of the ML4Astro International Conference 30 May - 1 Jun 2022
Gespeichert in:
| Weitere Verfasser: | , , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cham
Springer International Publishing
2023
Cham Springer |
| Ausgabe: | 1st ed. 2023 |
| Schriftenreihe: | Astrophysics and Space Science Proceedings
60 |
| Schlagworte: | |
| Online-Zugang: | TUM01 UBM01 UBT01 UBY01 Volltext |
| Beschreibung: | 1 Online-Ressource (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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| 700 | 1 | |a Schilliro, Francesco |4 edt | |
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| author2_variant | f b fb s r sr e s es f s fs |
| author_facet | Bufano, Filomena Riggi, Simone Sciacca, Eva Schilliro, Francesco |
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| dewey-full | 523.01 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 523 - Specific celestial bodies and phenomena |
| dewey-raw | 523.01 |
| dewey-search | 523.01 |
| dewey-sort | 3523.01 |
| dewey-tens | 520 - Astronomy and allied sciences |
| discipline | Physik |
| discipline_str_mv | Physik |
| doi_str_mv | 10.1007/978-3-031-34167-0 |
| edition | 1st ed. 2023 |
| format | Electronic eBook |
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| illustrated | Not Illustrated |
| index_date | 2024-07-03T23:02:46Z |
| indexdate | 2024-07-10T10:05:56Z |
| institution | BVB |
| isbn | 9783031341670 |
| issn | 1570-6605 |
| language | English |
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| publishDate | 2023 |
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| series2 | Astrophysics and Space Science Proceedings |
| spelling | Machine Learning for Astrophysics Proceedings of the ML4Astro International Conference 30 May - 1 Jun 2022 edited by Filomena Bufano, Simone Riggi, Eva Sciacca, Francesco Schilliro 1st ed. 2023 Cham Springer International Publishing 2023 Cham Springer 1 Online-Ressource (XIV, 211 p. 52 illus., 47 illus. in color) txt rdacontent c rdamedia cr rdacarrier Astrophysics and Space Science Proceedings 60 1570-6605 Astrophysics Machine Learning Artificial Intelligence Astronomy, Observations and Techniques Machine learning Artificial intelligence Astronomy / Observations Bufano, Filomena edt Riggi, Simone edt Sciacca, Eva edt Schilliro, Francesco edt Erscheint auch als Druck-Ausgabe 978-3-031-34166-3 Erscheint auch als Druck-Ausgabe 978-3-031-34168-7 Erscheint auch als Druck-Ausgabe 978-3-031-34169-4 https://doi.org/10.1007/978-3-031-34167-0 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Machine Learning for Astrophysics Proceedings of the ML4Astro International Conference 30 May - 1 Jun 2022 Astrophysics Machine Learning Artificial Intelligence Astronomy, Observations and Techniques Machine learning Artificial intelligence Astronomy / Observations |
| title | Machine Learning for Astrophysics Proceedings of the ML4Astro International Conference 30 May - 1 Jun 2022 |
| title_auth | Machine Learning for Astrophysics Proceedings of the ML4Astro International Conference 30 May - 1 Jun 2022 |
| title_exact_search | Machine Learning for Astrophysics Proceedings of the ML4Astro International Conference 30 May - 1 Jun 2022 |
| title_exact_search_txtP | Machine Learning for Astrophysics Proceedings of the ML4Astro International Conference 30 May - 1 Jun 2022 |
| title_full | Machine Learning for Astrophysics Proceedings of the ML4Astro International Conference 30 May - 1 Jun 2022 edited by Filomena Bufano, Simone Riggi, Eva Sciacca, Francesco Schilliro |
| title_fullStr | Machine Learning for Astrophysics Proceedings of the ML4Astro International Conference 30 May - 1 Jun 2022 edited by Filomena Bufano, Simone Riggi, Eva Sciacca, Francesco Schilliro |
| title_full_unstemmed | Machine Learning for Astrophysics Proceedings of the ML4Astro International Conference 30 May - 1 Jun 2022 edited by Filomena Bufano, Simone Riggi, Eva Sciacca, Francesco Schilliro |
| title_short | Machine Learning for Astrophysics |
| title_sort | machine learning for astrophysics proceedings of the ml4astro international conference 30 may 1 jun 2022 |
| title_sub | Proceedings of the ML4Astro International Conference 30 May - 1 Jun 2022 |
| topic | Astrophysics Machine Learning Artificial Intelligence Astronomy, Observations and Techniques Machine learning Artificial intelligence Astronomy / Observations |
| topic_facet | Astrophysics Machine Learning Artificial Intelligence Astronomy, Observations and Techniques Machine learning Artificial intelligence Astronomy / Observations |
| url | https://doi.org/10.1007/978-3-031-34167-0 |
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