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Deep Sets based Neural Networks for Impact Parameter Flavour Tagging in ATLAS
This work introduces a new architecture for Flavour Tagging based on Deep Sets, which models the jet as a set of tracks, in order to identify the experimental signatures of jets containing heavy flavour hadrons using the impact parameters and kinematics of the tracks. This approach is an evolution w...
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| Lenguaje: | eng |
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2020
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| Acceso en línea: | http://cds.cern.ch/record/2718948 |