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Found 3 papers, 1 papers with code
Enabling Efficient and Flexible Interpretability of Data-driven Anomaly Detection in Industrial Processes with AcME-AD
While Machine Learning has become crucial for Industry 4. 0, its opaque nature hinders trust and impedes the transformation of valuable insights into actionable decision, a challenge exacerbated in the evolving Industry 5. 0 with its human-centric focus.
AcME-AD: Accelerated Model Explanations for Anomaly Detection
Pursuing fast and robust interpretability in Anomaly Detection is crucial, especially due to its significance in practical applications.
AcME -- Accelerated Model-agnostic Explanations: Fast Whitening of the Machine-Learning Black Box
In the context of human-in-the-loop Machine Learning applications, like Decision Support Systems, interpretability approaches should provide actionable insights without making the users wait.
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