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GroomRL: jet grooming through reinforcement learning
<!--HTML-->We introduce a novel implementation of a reinforcement learning algorithm which is adapted to the problem of jet grooming, a crucial component of jet physics at hadron colliders. We show that the grooming policies trained using a Deep Q-Network model outperform state-of-the-art tool...
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| Lenguaje: | eng |
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2019
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| Acceso en línea: | http://cds.cern.ch/record/2672625 |