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Data Augmentation at the LHC through Analysis-specific Fast Simulation with Deep Learning
We present a fast simulation application based on a Deep Neural Network, designed to create large analysis-specific datasets. Taking as an example the generation of W+jet events produced in sqrt(s)= 13 TeV proton-proton collisions, we train a neural network to model detector resolution effects as a...
| Autores principales: | , , , , |
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| Lenguaje: | eng |
| Publicado: |
2020
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| Materias: | |
| Acceso en línea: | http://cds.cern.ch/record/2742834 |