Hyperparameter choice strongly alters the quality and composition of Monte Carlo Dropout and IVON uncertainty estimates for PPG-based AF and blood pressure models, and per-class calibration can differ sharply from global calibration.
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Uncertainty quantification with approximate variational learning for wearable photoplethysmography prediction tasks
Hyperparameter choice strongly alters the quality and composition of Monte Carlo Dropout and IVON uncertainty estimates for PPG-based AF and blood pressure models, and per-class calibration can differ sharply from global calibration.