Cargando…
Fast Simulation of a High Granularity Calorimeter by Generative Adversarial Networks
We present the 3DGAN for the simulation of a future high granularity calorimeter output as three-dimensional images. We prove the efficacy of Generative Adversarial Networks (GANs) for generating scientific data while retaining a high level of accuracy for diverse metrics across a large range of inp...
| Autores principales: | , , , |
|---|---|
| Lenguaje: | eng |
| Publicado: |
2021
|
| Materias: | |
| Acceso en línea: | https://dx.doi.org/10.1140/epjc/s10052-022-10258-4 http://cds.cern.ch/record/2782581 |