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Transformer models for heavy flavor jet identification
During Run2 of the Large Hadron Collider (LHC), deep-learning-based algorithms were established and led to a significantly improved heavy flavor (b and c) jet tagging performance. In the scope of large-radius boosted jets like top-quark jets, Graph Neural Network (GNN) based models, e.g., ParticleNe...
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| Lenguaje: | eng |
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2022
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| Acceso en línea: | http://cds.cern.ch/record/2839920 |