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ExplainableAD aims to develop a system for detecting complex anomalies in data streams using advanced deep learning techniques. It focuses on providing understandable insights to users, enhancing security and operational efficiency across various sectors, including finance and healthcare.
In the ExplainableAD project, we address the problem of eXplainable Anomaly Detection (XAD) on data streams with evolving, previously unknown, complex anomaly types.
To bridge the gap between growing demands in the data industry and severely limited industry-grade solutions available today, we propose a breakthrough XAD system that offers unprecedented capabilities for safeguarding digital services.
To this end, it seamlessly integrates deep learning-based anomaly detection (AD), which unlocks t…
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