In this seminar I will present some recent ideas in machine learning for model independent anomaly detection in high energy physics data. In particular I will discuss models at the interception of machine learning and hypothesis testing, specifically leveraging the Neyman-Pearson lemma. I will conclude showing some preliminary experimental results on toy and simulated data.

To participate: University of Genoa Teams group number 1npbr0h (if you have a Teams Unige account, you can access with the code. If you only have an INFN Teams account, write to simone.marzani@ge.infn.it to be added as a guest).