VACE learns compact directionally coherent representations for multivariate time series anomaly detection via velocity-consistency training and reports state-of-the-art results on TSB-AD-M.
Understanding contrastive representation learning through alignment and uniformity on the hypersphere
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VACE: Learning Geometrically Structured Representations for Time Series Anomaly Detection
VACE learns compact directionally coherent representations for multivariate time series anomaly detection via velocity-consistency training and reports state-of-the-art results on TSB-AD-M.