POST: Prior-Observation Adversarial Learning of Spatio-Temporal Associations for Multivariate Time Series Anomaly Detection

In three linesPOST introduces an adversarial learning framework for multivariate time series anomaly detection. The model combines graph neural networks with minimax optimization over adjacency matrices to address spatial over-generalization. Evaluation on public and synthetic benchmarks with channel-wise anomaly localization.

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