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Reimagining Anomalies: What If Anomalies Were Normal?
Deep learning-based methods have achieved a breakthrough in image anomaly detection, but their complexity introduces a considerable challenge to understanding why an instance is predicted to be anomalous.
Wisdom of the Contexts: Active Ensemble Learning for Contextual Anomaly Detection
Furthermore, the results support our initial hypothesis that there is no single perfect context that successfully uncovers all kinds of contextual anomalies, and leveraging the "wisdom" of multiple contexts is necessary.
No Free Lunch But A Cheaper Supper: A General Framework for Streaming Anomaly Detection
To date, there exists no single general method that has been shown to outperform the others across different anomaly types, use cases and datasets.
A data-driven approach for discovering heat load patterns in district heating
Understanding the heat usage of customers is crucial for effective district heating operations and management.
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