Integrates Dirichlet-based class probability modeling into MC Dropout to improve calibration of uncertainty estimates while preserving efficiency.
Predictive uncertainty estimation via prior networks
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Dirichlet-Based Monte Carlo Dropout for Uncertainty Estimation in Neural Networks
Integrates Dirichlet-based class probability modeling into MC Dropout to improve calibration of uncertainty estimates while preserving efficiency.