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Machine Learning for Particle Identification and Deep Generative Models Towards Fast Simulations for the ALICE Transition Radiation Detector at CERN
This Masters thesis outlines the application of machine learning techniques, predominantly deep learning techniques, towards certain aspects of particle physics. Its two main aims: particle identification and high energy physics detector simulations are pertinent to research avenues pursued by physi...
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| Lenguaje: | eng |
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2020
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| Acceso en línea: | http://cds.cern.ch/record/2707778 |