Domain Generalization with Machine Learning in the NOvA Experiment:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cham
Springer Nature Switzerland
2023
Cham Springer |
| Ausgabe: | 1st ed. 2023 |
| Schriftenreihe: | Springer Theses, Recognizing Outstanding Ph.D. Research
|
| Schlagworte: | |
| Online-Zugang: | TUM01 UBM01 UBT01 UBY01 Volltext |
| Beschreibung: | 1 Online-Ressource (XI, 170 p. 73 illus., 63 illus. in color) |
| ISBN: | 9783031435836 |
| ISSN: | 2190-5061 |
| DOI: | 10.1007/978-3-031-43583-6 |
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Datensatz im Suchindex
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| discipline_str_mv | Physik |
| doi_str_mv | 10.1007/978-3-031-43583-6 |
| edition | 1st ed. 2023 |
| format | Electronic eBook |
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| id | DE-604.BV049442011 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T23:12:10Z |
| indexdate | 2024-07-10T10:07:15Z |
| institution | BVB |
| isbn | 9783031435836 |
| issn | 2190-5061 |
| language | English |
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| physical | 1 Online-Ressource (XI, 170 p. 73 illus., 63 illus. in color) |
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| publishDate | 2023 |
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| publisher | Springer Nature Switzerland Springer |
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| series2 | Springer Theses, Recognizing Outstanding Ph.D. Research |
| spelling | Sutton, Andrew T.C. Verfasser aut Domain Generalization with Machine Learning in the NOvA Experiment by Andrew T.C. Sutton 1st ed. 2023 Cham Springer Nature Switzerland 2023 Cham Springer 1 Online-Ressource (XI, 170 p. 73 illus., 63 illus. in color) txt rdacontent c rdamedia cr rdacarrier Springer Theses, Recognizing Outstanding Ph.D. Research 2190-5061 Particle Physics Accelerator Physics Measurement Science and Instrumentation Machine Learning Computational Physics and Simulations Particles (Nuclear physics) Particle accelerators Measurement Measuring instruments Machine learning Mathematical physics Computer simulation Erscheint auch als Druck-Ausgabe 978-3-031-43582-9 Erscheint auch als Druck-Ausgabe 978-3-031-43584-3 Erscheint auch als Druck-Ausgabe 978-3-031-43585-0 https://doi.org/10.1007/978-3-031-43583-6 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Sutton, Andrew T.C Domain Generalization with Machine Learning in the NOvA Experiment Particle Physics Accelerator Physics Measurement Science and Instrumentation Machine Learning Computational Physics and Simulations Particles (Nuclear physics) Particle accelerators Measurement Measuring instruments Machine learning Mathematical physics Computer simulation |
| title | Domain Generalization with Machine Learning in the NOvA Experiment |
| title_auth | Domain Generalization with Machine Learning in the NOvA Experiment |
| title_exact_search | Domain Generalization with Machine Learning in the NOvA Experiment |
| title_exact_search_txtP | Domain Generalization with Machine Learning in the NOvA Experiment |
| title_full | Domain Generalization with Machine Learning in the NOvA Experiment by Andrew T.C. Sutton |
| title_fullStr | Domain Generalization with Machine Learning in the NOvA Experiment by Andrew T.C. Sutton |
| title_full_unstemmed | Domain Generalization with Machine Learning in the NOvA Experiment by Andrew T.C. Sutton |
| title_short | Domain Generalization with Machine Learning in the NOvA Experiment |
| title_sort | domain generalization with machine learning in the nova experiment |
| topic | Particle Physics Accelerator Physics Measurement Science and Instrumentation Machine Learning Computational Physics and Simulations Particles (Nuclear physics) Particle accelerators Measurement Measuring instruments Machine learning Mathematical physics Computer simulation |
| topic_facet | Particle Physics Accelerator Physics Measurement Science and Instrumentation Machine Learning Computational Physics and Simulations Particles (Nuclear physics) Particle accelerators Measurement Measuring instruments Machine learning Mathematical physics Computer simulation |
| url | https://doi.org/10.1007/978-3-031-43583-6 |
| work_keys_str_mv | AT suttonandrewtc domaingeneralizationwithmachinelearninginthenovaexperiment |