A method for approximating optimal statistical significances with machine-learned likelihoods
Abstract Machine-learning techniques have become fundamental in high-energy physics and, for new physics searches, it is crucial to know their performance in terms of experimental sensitivity, understood as the statistical significance of the signal-plus-background hypothesis over the background-onl...
| Hlavní autoři: | , , , , , , |
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| Médium: | Článek |
| Jazyk: | English |
| Vydáno: |
SpringerOpen
2022-11-01
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| Edice: | European Physical Journal C: Particles and Fields |
| On-line přístup: | https://doi.org/10.1140/epjc/s10052-022-10944-3 |