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Three dimensional Generative Adversarial Networks for fast simulation
We present the first application of three-dimensional convolutional Generative Adversarial Network to High Energy Physics simulation. We generate three-dimensional images of particles depositing energy in high granularity calorimeters. This is the first time such an approach is taken in HEP where mo...
| Autores principales: | , , , , , |
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| Lenguaje: | eng |
| Publicado: |
2018
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| Materias: | |
| Acceso en línea: | https://dx.doi.org/10.1088/1742-6596/1085/3/032016 http://cds.cern.ch/record/2665775 |