Anomalies in eight popular MTSAD benchmarks are predominantly univariate, with no cross-channel ruptures occurring without accompanying univariate deviations, rendering the benchmarks unsuitable for testing cross-channel modeling.
An Evaluation of Anomaly Detection and Diagno- sis in Multivariate Time Series
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Introduces a cyclic-dynamics dataset for industrial MTSAD and benchmarks federated anomaly detection methods on it and a public dataset.
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Anomalies in Multivariate Time Series Benchmarks Are Mostly Univariate
Anomalies in eight popular MTSAD benchmarks are predominantly univariate, with no cross-channel ruptures occurring without accompanying univariate deviations, rendering the benchmarks unsuitable for testing cross-channel modeling.
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Federated Learning for Multivariate Time Series Anomaly Detection in Industrial Automation
Introduces a cyclic-dynamics dataset for industrial MTSAD and benchmarks federated anomaly detection methods on it and a public dataset.