65 citations · 236 across the 15 of their papers we have counts for
3 papers · 1 filter
Non-resonant Anomaly Detection with Background Extrapolation
Kehang Bai, Radha Mastandrea, Benjamin Nachman
Complete anomaly detection strategies that are both signal sensitive and compatible with background estimation have largely focused on resonant signals. Non-resonant new physics sc…
Flows for Flows: Morphing one Dataset into another with Maximum Likelihood Estimation
Tobias Golling, Samuel Klein, Radha Mastandrea +2
Many components of data analysis in high energy physics and beyond require morphing one dataset into another. This is commonly solved via reweighting, but there are many advantages…
The Interplay of Machine Learning--based Resonant Anomaly Detection Methods
Tobias Golling, Gregor Kasieczka, Claudius Krause +6
Machine learning--based anomaly detection (AD) methods are promising tools for extending the coverage of searches for physics beyond the Standard Model (BSM). One class of AD metho…