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The chaos of MTSAD research gets a little tamer with a new taxonomy that exposes the field's hidden convergence on Transformers and reconstruction, hinting at where the next breakthroughs will come from.
Deep learning's dominance in time series anomaly detection may be overstated: a carefully evaluated PCA baseline rivals the performance of the widely-used OmniAnomaly.
Ditch slow, unstable AR estimation: neural nets offer a 12x speed boost and better convergence, without sacrificing interpretability.
