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Obermair Christoph
Obermair Christoph
Graz University of Technology, CERN
在 cern.ch 的电子邮件经过验证
标题
引用次数
引用次数
年份
Explainable machine learning for breakdown prediction in high gradient rf cavities
O Christoph, CM Thomas, A Andrea, M William, F Lukas, F Lorenz, ...
Phys. Rev. Accel. Beams 25 (10), 21, 2022
22*2022
Example or prototype? learning concept-based explanations in time-series
C Obermair, A Fuchs, F Pernkopf, L Felsberger, A Apollonio, D Wollmann
Asian Conference on Machine Learning, 816-831, 2023
52023
JACoW: Machine Learning Models for Breakdown Prediction in RF Cavities for Accelerators
C Obermair, A Apollonio, W Wuensch, L Felsberger, T Cartier-Michaud, ...
JACoW IPAC 2021, 1068-1071, 2021
52021
JACoW: Machine Learning with a Hybrid Model for Monitoring of the Protection Systems of the LHC
C Obermair, A Verweij, A Apollonio, F Pernkopf, M Maciejewski, ...
JACoW IPAC 2021, 1072-1075, 2021
32021
Interpretable Anomaly Detection in the LHC Main Dipole Circuits with Non-Negative Matrix Factorization
C Obermair, A Apollonio, Z Charifoulline, L Felsberger, M Janitschke, ...
IEEE Transactions on Applied Superconductivity, 2024
12024
Workshop on Dust Charging and Beam-Dust Interaction in Particle Accelerators
MR Blaszkiewicz, X Wang, C Obermair, GJ Rosaz, L Felsberger, ...
12023
Signal monitoring for the LHC-Development of an application for analyzing the main quadrupole busbar resistance
C Obermair
12018
Anomaly Detection in Conditioning Procedures
M Hofmann-Wellenhof, C Obermair
2022
Data Augmentation for Breakdown Prediction in CLIC RF Cavities
H Bovbjerg, A Apollonio, C Obermair, T Cartier-Michaud, D Wollmann, ...
JACoW IPAC 2022, 1553-1556, 2022
2022
Extension of Signal Monitoring Applications with Machine Learning
C Obermair
Graz, Tech. U., 2020
2020
Interpretable Fault Prediction for CERN Energy Frontier Colliders
C Obermair
Graz University of Technology (AT), 0
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