Anomaly detection using Deep Autoencoders for the assessment of the quality of the data acquired by the CMS experiment
EPJ Web Conf., 214 (2019) 06008
Published online: 2019-09-17
Articles citing this article
The Citing articles tool gives a list of articles citing the current article.
The citing articles come from EDP Sciences database, as well as other publishers participating in CrossRef Cited-by Linking Program. You can set up your personal account to receive an email alert each time this article is cited by a new article (see the menu on the right-hand side of the abstract page).
Cited article:
This article has been cited by the following article(s):
Data Quality Monitoring for the Hadron Calorimeters Using Transfer Learning for Anomaly Detection
Mulugeta Weldezgina Asres, Christian Walter Omlin, Long Wang, David Yu, Pavel Parygin and Jay DittmannSensors 25 (11) 3475 (2025)
https://doi.org/10.3390/s25113475
Towards Real-Time Machine Learning-Based Signal/Background Selection in the CMS Detector Using Quantized Neural Networks and Input Data Reduction
Arijana Burazin Mišura, Josip Musić, Marina Prvan and Damir LelasApplied Sciences 14 (4) 1559 (2024)
https://doi.org/10.3390/app14041559
36 (2024)
https://doi.org/10.1109/SOSE62659.2024.10620930
Application of deep learning in top pair and single top quark production at the LHC
Ijaz Ahmed, Anwar Zada, Muhammad Waqas and M. U. AshrafThe European Physical Journal Plus 138 (9) (2023)
https://doi.org/10.1140/epjp/s13360-023-04409-z
Spatio-Temporal Anomaly Detection with Graph Networks for Data Quality Monitoring of the Hadron Calorimeter
Mulugeta Weldezgina Asres, Christian Walter Omlin, Long Wang, David Yu, Pavel Parygin, Jay Dittmann, Georgia Karapostoli, Markus Seidel, Rosamaria Venditti, Luka Lambrecht, Emanuele Usai, Muhammad Ahmad, Javier Fernandez Menendez and Kaori MaeshimaSensors 23 (24) 9679 (2023)
https://doi.org/10.3390/s23249679
NFAD: fixing anomaly detection using normalizing flows
Artem Ryzhikov, Maxim Borisyak, Andrey Ustyuzhanin and Denis DerkachPeerJ Computer Science 7 e757 (2021)
https://doi.org/10.7717/peerj-cs.757
End-to-End Sinkhorn Autoencoder With Noise Generator
Kamil Deja, Jan Dubinski, Piotr Nowak, et al.IEEE Access 9 7211 (2021)
https://doi.org/10.1109/ACCESS.2020.3048622
364 (2021)
https://doi.org/10.1109/PIC53636.2021.9687034
The Phase-2 Upgrade of the Hardware Trigger of CMS at the LHC
M. JeitlerJournal of Instrumentation 15 (09) C09009 (2020)
https://doi.org/10.1088/1748-0221/15/09/C09009
The Data Quality Monitoring Software for the CMS experiment at the LHC: past, present and future
Virginia Azzolini, Besien Broen van, Dmitrijus Bugelskis, et al.EPJ Web of Conferences 214 02003 (2019)
https://doi.org/10.1051/epjconf/201921402003