GE: MODERN MACHINE LEARNING WITH JET IMAGES FOR HIGH ENERGY PHYSICS 
 ELENCO COMPLETO 

DATA: 10-11-2017

SEZIONE DI GENOVA
(E. Santopinto) Seminario di Fenomenologia delle particelle elementari, a carattere divulgativo. Evento congiunto con l'Universita' di Genova. Speaker: Ben Nachmann (Berkeley) Modern machine learning (ML) has introduced a new and powerful toolkit to High Energy Physics. While only a small number of these techniques are currently used in practice, research and development centered around modern ML has exploded over the last year(s). I will highlight recent advances with a focus on jets: collimated sprays of particles resulting from quarks and gluons produced at high energy. Themselves defined by unsupervised learning algorithms, jets are a prime benchmark for state-of-the-art ML applications and innovations. For example, I will show how deep learning has been applied to jets for classification, regression, and generation. These tools hold immense potential, but incorporating domain-specific knowledge is necessary for optimal performance. In addition, studying what the machines are learning is critical for robustness and may even help us learn new physics!


 SITO COLLEGATO 
https://agenda.infn.it/conferenceDisplay.py?confId=14529

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