Cargando…
Physics and Computing Performance of the Exa.TrkX TrackML Pipeline
<!--HTML-->The Exa.TrkX project has applied geometric learning concepts such as metric learning and graph neural networks to HEP particle tracking. The Exa.TrkX tracking pipeline clusters detector measurements to form track candidates and selects track candidates with competitive efficiency an...
Autor principal: | Murnane, Daniel Thomas |
---|---|
Lenguaje: | eng |
Publicado: |
2021
|
Materias: | |
Acceso en línea: | http://cds.cern.ch/record/2767568 |
Ejemplares similares
-
Applying and optimizing the Exa.TrkX Pipeline on the OpenDataDetector with ACTS
por: Calafiura, Paolo, et al.
Publicado: (2022) -
TrackML : The High Energy Physics Tracking Challenge
por: Rousseau, David
Publicado: (2018) -
The TrackML high-energy physics tracking challenge on Kaggle
por: Kiehn, Moritz, et al.
Publicado: (2019) -
Kinematic Analysis of TrackML Challenge Submissions
por: Ramey, Emily Ashlynne
Publicado: (2018) -
TrackML : a tracking Machine Learning challenge
por: Golling, Tobias, et al.
Publicado: (2019)