Nov 19, 2017 · In this paper, the problem of identifying channels in which anomalies occurred is considered. We introduce a generic deep learning model and ...

In this paper, the problem of identifying channels in which anomalies occurred is considered. We introduce a generic deep learning model and prove that, under ...

In this work, we described a deep learning approach for inferring cause of data anomalies. While developed with the CMS experiment at CERN in mind, we use ...

Introduction. Daily operation of a large-scale experiment is a resource consuming task, particularly from the perspectives of routine data quality ...

A generic deep learning model is introduced and it is proved that, under reasonable assumptions, the model learns to identify 'channels' which are affected ...

In this paper, the problem of identifying channels in which anomalies occurred is considered. We introduce a generic deep learning model and prove that, under ...

Distributions of predictions returned by NN branches build on features from a) calorimiter, b) particle flow jets, c) muons, d) photons channels.

In this paper, the problem of identifying channels in which anomalies occurred is considered. We introduce a generic deep learning model and prove that, under ...

Apr 26, 2024 · Anomaly detection is indicated by entering the relevant moment “t” in the anomaly column of the prediction outputs. Specifically, if the actual ...

We introduce a generic deep learning model and prove that, under reasonable assumptions, the model learns to identify 'channels' which are affected by an ...