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Large-scale distributed training applied to generative adversarial networks for calorimeter simulation
In recent years, several studies have demonstrated the benefit of using deep learning to solve typical tasks related to high energy physics data taking and analysis. In particular, generative adversarial networks are a good candidate to supplement the simulation of the detector response in a collide...
| Autores principales: | , , , , , , , |
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| Lenguaje: | eng |
| Publicado: |
2019
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| Materias: | |
| Acceso en línea: | https://dx.doi.org/10.1051/epjconf/201921406025 http://cds.cern.ch/record/2699586 |