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We introduce Neural Contextual Anomaly Detection (NCAD), a framework for anomaly detection on time series that scales seamlessly from the unsupervised to supervised setting, and is applicable to both univariate and multivariate time series.
Deep Semi-Supervised Anomaly Detection
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Deep anomaly detection with outlier exposure
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Learning Ensembles of Anomaly Detectors on Synthetic Data
Smolyakov, D., Sviridenko, N., Ishimtsev, V., Burikov, E., and Burnaev, E · 2019
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Timeseries anomaly detection using temporal hierarchical one-class network
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