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Zero-shot foundation models may excel at capturing temporal dynamics but fall short in reliably detecting multivariate anomalies, revealing a critical gap in their application.
Latent SDEs reveal a powerful new framework for detecting anomalies in multivariate time series, outperforming traditional methods in the face of data irregularities and sparsity.