44 citations · 216 across the 15 of their papers we have counts for
4 papers · 1 filter
Goodness of fit by Neyman-Pearson testing
Gaia Grosso, Marco Letizia, Maurizio Pierini +1
The Neyman-Pearson strategy for hypothesis testing can be employed for goodness of fit if the alternative hypothesis is selected from data by exploring a rich parametrised family o…
Fast kernel methods for Data Quality Monitoring as a goodness-of-fit test
Gaia Grosso, Nicolò Lai, Marco Letizia +5
We here propose a machine learning approach for monitoring particle detectors in real-time. The goal is to assess the compatibility of incoming experimental data with a reference d…
Comparison of Affine and Rational Quadratic Spline Coupling and Autoregressive Flows through Robust Statistical Tests
Andrea Coccaro, Marco Letizia, Humberto Reyes-Gonzalez +1
Normalizing flows have emerged as a powerful brand of generative models, as they not only allow for efficient sampling of complicated target distributions but also deliver density…
A fast and flexible machine learning approach to data quality monitoring
Gaia Grosso, Nicolò Lai, Marco Letizia +4
We present a machine learning based approach for real-time monitoring of particle detectors. The proposed strategy evaluates the compatibility between incoming batches of experimen…