Introduces the ECUAS_n family of proper scoring rules for evaluating uncertainty-augmented systems, where n tunes the trade-off between prediction accuracy costs and uncertainty quality.
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2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
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Aerodynamic pressure signals enable real-time, interpretable detection and severity classification of structural damage in elastic beam-like structures via CNN enhanced with physics insights and XAI.
citing papers explorer
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$ECUAS_n$: A family of metrics for principled evaluation of uncertainty-augmented systems
Introduces the ECUAS_n family of proper scoring rules for evaluating uncertainty-augmented systems, where n tunes the trade-off between prediction accuracy costs and uncertainty quality.
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Towards Interpretable Damage Detection based on Aerodynamic Pressure Measurements
Aerodynamic pressure signals enable real-time, interpretable detection and severity classification of structural damage in elastic beam-like structures via CNN enhanced with physics insights and XAI.