Learning likelihood ratios with neural network classifiers
Abstract The likelihood ratio is a crucial quantity for statistical inference in science that enables hypothesis testing, construction of confidence intervals, reweighting of distributions, and more. Many modern scientific applications, however, make use of data- or simulation-driven models for whic...
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| Principais autores: | , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
SpringerOpen
2024-02-01
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| coleção: | Journal of High Energy Physics |
| Assuntos: | |
| Acesso em linha: | https://doi.org/10.1007/JHEP02(2024)136 |
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