AINeutralarXiv – CS AI · 10h ago6/10
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CATCH: Channel-Aware multivariate Time Series Anomaly Detection via Frequency Patching
Researchers introduce CATCH, a novel framework for detecting anomalies in multivariate time series data using frequency patching and channel-aware mechanisms. The method achieves state-of-the-art performance across 22 datasets by improving detection of fine-grained frequency patterns while identifying relevant channel correlations through a Channel Fusion Module.