most citedThe model of an anomaly detector for HiLumi LHC magnets based on Recurrent Neural Networks and adaptive quantization

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cs.LG2017★ 22 cited

The model of an anomaly detector for HiLumi LHC magnets based on Recurrent Neural Networks and adaptive quantization

Maciej Wielgosz, Matej Mertik, Andrzej Skoczeń +1

This paper focuses on an examination of an applicability of Recurrent Neural Network models for detecting anomalous behavior of the CERN superconducting magnets. In order to conduc…