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ATLAS data analysis using a parallelized workflow on distributed cloud-based services with GPUs
We present a new implementation of simulation-based inference using data collected by the ATLAS experiment at the LHC. The method relies on large ensembles of deep neural networks to approximate the exact likelihood. Additional neural networks are introduced to model systematic uncertainties in the...
| Autores principales: | , , , , , |
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| Lenguaje: | eng |
| Publicado: |
2023
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| Materias: | |
| Acceso en línea: | http://cds.cern.ch/record/2858013 |