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End-to-End Physics Event Classification with the CMS Open Data: Applying Image-based Deep Learning on Detector Data to Directly Classify Collision Events at the LHC
This paper describes the construction of novel end-to-end image-based classifiers that directly leverage low-level simulated detector data to discriminate signal and background processes in proton–proton collision events at the Large Hadron Collider at CERN. To better understand what end-to-end clas...
| Autores principales: | , , , |
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| Lenguaje: | eng |
| Publicado: |
2018
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| Materias: | |
| Acceso en línea: | https://dx.doi.org/10.1007/s41781-020-00038-8 http://cds.cern.ch/record/2641646 |