PoS - Proceedings of Science
Volume 390 - 40th International Conference on High Energy physics (ICHEP2020) - Parallel: Beyond the Standard Model
Deep Learning Versatility in New Physics Searches
M. Crispim Romao
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Pre-published on: February 02, 2021
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Abstract
In this communication, we will discuss the application of Deep Learning models as a discriminant step to improve sensitivity at searches for new physics. Of particular interest, we will focus on the transferability of Deep Learning models, where a neural network trained to isolate a specific signal can still provide sensitivity when deriving upper limits on a different process. This is expanded to include a discussion on the versatility of Deep Learning models to provide enough sensitivity in cases where the signal present in the sample does not follow the assumptions of an analysis.
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