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Machine learning for top quark physics at the edge in LHC pp collisions with ATLAS and CMS
Illustration of most advanced and performant ML techniques used in top quark physics measurements: from top reconstruction to signal to background rejection methods to top-jet-tagging.
| Autor principal: | |
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| Lenguaje: | eng |
| Publicado: |
2021
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| Materias: | |
| Acceso en línea: | http://cds.cern.ch/record/2784386 |
| _version_ | 1780972098176417792 |
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| author | Nellist, Clara |
| author_facet | Nellist, Clara |
| author_sort | Nellist, Clara |
| collection | CERN |
| description | Illustration of most advanced and performant ML techniques used in top quark physics measurements: from top reconstruction to signal to background rejection methods to top-jet-tagging. |
| id | cern-2784386 |
| institution | Organización Europea para la Investigación Nuclear |
| language | eng |
| publishDate | 2021 |
| record_format | invenio |
| spelling | cern-27843862021-10-17T21:24:53Zhttp://cds.cern.ch/record/2784386engNellist, ClaraMachine learning for top quark physics at the edge in LHC pp collisions with ATLAS and CMSParticle Physics - ExperimentIllustration of most advanced and performant ML techniques used in top quark physics measurements: from top reconstruction to signal to background rejection methods to top-jet-tagging.ATL-PHYS-SLIDE-2021-619oai:cds.cern.ch:27843862021-10-17 |
| spellingShingle | Particle Physics - Experiment Nellist, Clara Machine learning for top quark physics at the edge in LHC pp collisions with ATLAS and CMS |
| title | Machine learning for top quark physics at the edge in LHC pp collisions with ATLAS and CMS |
| title_full | Machine learning for top quark physics at the edge in LHC pp collisions with ATLAS and CMS |
| title_fullStr | Machine learning for top quark physics at the edge in LHC pp collisions with ATLAS and CMS |
| title_full_unstemmed | Machine learning for top quark physics at the edge in LHC pp collisions with ATLAS and CMS |
| title_short | Machine learning for top quark physics at the edge in LHC pp collisions with ATLAS and CMS |
| title_sort | machine learning for top quark physics at the edge in lhc pp collisions with atlas and cms |
| topic | Particle Physics - Experiment |
| url | http://cds.cern.ch/record/2784386 |
| work_keys_str_mv | AT nellistclara machinelearningfortopquarkphysicsattheedgeinlhcppcollisionswithatlasandcms |