Li-Rong Jin

A dual-path multi-view framework for deployment-oriented time series anomaly detection

Deployment Oriented Dual Path Multi View Anomaly Detection (DP-MVAD), a deployment-efficient framework designed for complex non-stationary conditions, achieves trend-perturbation disentanglement through a conditionally identifiable dual-path approximation and ensures robust cross-scenario representations.