AIBullisharXiv – CS AI · 18h ago6/10
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PAI: Preserving Amplitude Information in Representation-Based Time-Series Anomaly Detection
Researchers propose PAI, a novel anomaly scoring scheme that addresses a critical limitation in representation-based time-series anomaly detection by explicitly preserving amplitude information in learned embeddings. The method achieves significant performance improvements, with average gains of 98.4% on TSB-AD-U-Eva and 36.8% on TAB UV datasets, suggesting that amplitude retention is crucial for robust anomaly detection.