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Optimising HEP parameter fits via Monte Carlo weight derivative regression
HEP event selection is traditionally considered a binary classification problem, involving the dichotomous categories of signal and background. In distribution fits for particle masses or couplings, however, signal events are not all equivalent, as the signal differential cross section has different...
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| Lenguaje: | eng |
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2020
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| Acceso en línea: | https://dx.doi.org/10.1051/epjconf/202024506038 http://cds.cern.ch/record/2715330 |