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Multidimensional Deconvolution with Profiling
Huanbiao Zhu, Krish Desai, Mikael Kuusela +3
In many experimental contexts, it is necessary to statistically remove the impact of instrumental effects in order to physically interpret measurements. This task has been extensiv…
Toward Model-Agnostic Detection of New Physics Using Data-Driven Signal Regions
Soheun Yi, John Alison, Mikael Kuusela
In the search for new particles in high-energy physics, it is crucial to select the Signal Region (SR) in such a way that it is enriched with signal events if they are present. Whi…
Robust semi-parametric signal detection in particle physics with classifiers decorrelated via optimal transport
Purvasha Chakravarti, Lucas Kania, Olaf Behnke +2
Searches for signals of new physics in particle physics are usually done by training a supervised classifier to separate a signal model from the known Standard Model physics (also…