Volume 478 - 12th Large Hadron Collider Physics Conference (LHCP2024) - Performance
Machine learning in online/offline calibration and reconstruction at the LHC
C. Sonnabend* and  On behalf of the ALICE, ATLAS, CMS and LHCb collaborations
*: corresponding author
Full text: pdf
Pre-published on: December 31, 2024
Published on: —
Abstract
These proceedings report on the status and use of machine learning algorithms and especially neural networks in online and offline reconstruction and calibration for the four major experiments at CERN. The paper provides an overview and specific examples, ranging from raw data readout to final offline calibrations.
DOI: https://doi.org/10.22323/1.478.0151
How to cite

Metadata are provided both in article format (very similar to INSPIRE) as this helps creating very compact bibliographies which can be beneficial to authors and readers, and in proceeding format which is more detailed and complete.

Open Access
Creative Commons LicenseCopyright owned by the author(s) under the term of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.