CERN Accelerating science

Talk
Title	Machine learning for surface prediction in ACTS
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Author(s)	Huth, Benjamin (speaker) (Universität Regensburg)
Corporate author(s)	CERN. Geneva
Imprint	2021-05-19. - 819.
Series	(Conferences) (25th International Conference on Computing in High Energy & Nuclear Physics)
Lecture note	on 2021-05-19T11:03:00
Subject category	Conferences
Abstract	We present an ongoing R&D; activity for machine-learning-assisted navigation through detectors to be used for track reconstruction. We investigate different approaches of training neural networks for surface prediction and compare their results. This work is carried out in the context of the ACTS tracking toolkit.
Copyright/License	© 2021-2024 CERN
Submitted by	paul.james.laycock@cern.ch