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Charged particle tracking via edge-classifying interaction networks

<!--HTML-->Recent work has demonstrated that geometric deep learning methods such as graph neural networks (GNNs) are well-suited to address a variety of recon- struction problems in HEP. In particular, tracker events are naturally repre- sented as graphs by identifying hits as nodes and track...

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Detalles Bibliográficos
Autor principal: DeZoort, Gage
Lenguaje:eng
Publicado: 2021
Materias:
Acceso en línea:http://cds.cern.ch/record/2767798

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