PLAG boosts tabular anomaly detection by using pseudo-label-guided synthetic anomaly generation with a two-stage filter, achieving SOTA results and lifting F1 scores by 0.08-0.21 when added to existing detectors.
Copod: copula-based outlier detection,
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Extending Matrix Profile to multidimensional time series yields the only method among 19 baselines that maintains high anomaly detection performance across unsupervised, supervised, and semi-supervised regimes on 119 datasets.
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Enhancing Tabular Anomaly Detection via Pseudo-Label-Guided Generation
PLAG boosts tabular anomaly detection by using pseudo-label-guided synthetic anomaly generation with a two-stage filter, achieving SOTA results and lifting F1 scores by 0.08-0.21 when added to existing detectors.
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Matrix Profile for Anomaly Detection on Multidimensional Time Series
Extending Matrix Profile to multidimensional time series yields the only method among 19 baselines that maintains high anomaly detection performance across unsupervised, supervised, and semi-supervised regimes on 119 datasets.