AI RESEARCH
Revisiting OmniAnomaly for Anomaly Detection: performance metrics and comparison with PCA-based models
arXiv CS.LG
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ArXi:2603.18985v1 Announce Type: cross Deep learning models have become the dominant approach for multivariate time series anomaly detection (MTSAD), often reporting substantial performance improvements over classical statistical methods. However, these gains are frequently evaluated under heterogeneous thresholding strategies and evaluation protocols, making fair comparisons difficult.