Domain Generalization with Machine Learning in the NOvA Experiment : Doctoral Thesis accepted by the University of Virginia, USA / Andrew T. C. Sutton
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| Autore: |
Sutton, Andrew T. C.
|
| Titolo: |
Domain Generalization with Machine Learning in the NOvA Experiment : Doctoral Thesis accepted by the University of Virginia, USA / Andrew T. C. Sutton
|
| Pubblicazione: | Cham, : Springer, 2023 |
| Descrizione fisica: | xi, 170 p. : ill. ; 24 cm |
| Soggetto topico: | 00A79 (77-XX) - Physics [MSC 2020] |
| 68-XX - Computer science [MSC 2020] | |
| 68Txx - Artificial intelligence [MSC 2020] | |
| 81V35 - Nuclear physics [MSC 2020] | |
| Soggetto non controllato: | 3-flavor analysis |
| Adversarial domain generalization | |
| Event reconstruction | |
| Machine learning in HEP | |
| NOvA experiment | |
| Neutrino Oscillation | |
| Particle identification | |
| Physics beyond the Standard Model | |
| Titolo autorizzato: | Domain Generalization with Machine Learning in the NOvA Experiment |
| Formato: | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione: | Inglese |
| Record Nr.: | VAN00286052 |
| Lo trovi qui: | Univ. Vanvitelli |
| Localizzazioni e accesso elettronico | https://doi.org/10.1007/978-3-031-43583-6 |
| Opac: | Controlla la disponibilità qui |
Serie:
Springer theses : recognizing outstanding Ph.D. research Berlin . -Springer , 2010-