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Deep generative models for fast shower simulation in ATLAS
The need for large scale and high fidelity simulated samples for the extensive physics program of the ATLAS experiment at the Large Hadron Collider motivates the development of new simulation techniques. Building on the recent success of deep learning algorithms, Variational Auto-Encoders and Genera...
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| Lenguaje: | eng |
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2018
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| Acceso en línea: | http://cds.cern.ch/record/2630433 |