Tuning Monte Carlo Dropout hyperparameters with GWO, BO, or PSO and adding a predictive-entropy loss term reportedly improves accuracy, uncertainty accuracy, and calibration by 2-3% over vanilla MCD.
In: 2023 24th International Conference on Digital Signal Processing (DSP), pp
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Enhancing Monte Carlo Dropout Performance for Uncertainty Quantification
Tuning Monte Carlo Dropout hyperparameters with GWO, BO, or PSO and adding a predictive-entropy loss term reportedly improves accuracy, uncertainty accuracy, and calibration by 2-3% over vanilla MCD.