arXiv (OAI Expanded)
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Optimal Transport for Efficient, Unsupervised Anomaly Detection on Industrial Data
Effective anomaly detection frameworks are a central pillar of the Industry 4.0 paradigm. In this paper, we introduce an Optimal Transport (OT)-based framework for anomaly detection, designed to detect deviations from normal behaviour in time-series sensor data. The OT-based method requires minimal
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