Artificial Intelligence at the Large Hadron Collider (1 de octubre de 2021)

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      Meeting ID: 675 3033 5605
      Passcode: 227617

[ABSTRACT]

Deep Learning approach to LHCb Calorimeter reconstruction using a Cellular Automaton Núria Valls Canudas, Xavier Vilasis Cardona, Míriam Calvo Gómez and Elisabet Golobardes Ribé EPJ Web Conf., 251 (2021) 04008 DOI: https://doi.org/10.1051/epjconf/202125104008

Artificial Intelligence Techniques, and in particular those related to Machine Learning, have become ubiquitous in the LHC experiments. They are applied at a wide range of different experimental activities like analysis or reconstruction.

In this 4th seminar of the Spanish LHC Network, Dr. Xavier Vilasís will review the application of Artificial Intelligence Techniques by the main experiments at the LHC: LHCb, ATLAS and CMS.

[BIO] Xavier Vilasís Cardona es Doctor en Física por la Universitat de Barcelona, Catedrático en La Salle, Universitat Ramon Llull, Investigador Principal del grupo Data Science for the Digital Society y miembro de la colaboración LHCb.

Artificial Intelligence at the Large Hadron Collider

por Xavier Vilasis-Cardona (DS4DS, La Salle - Universitat Ramon Llull)

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