Classical uncertainty quantification methods transfer to quantum machine learning; Bayesian quantum models and Gaussian dropout give the best-calibrated uncertainty estimates in small simulated experiments.
A rigorous and robust quantum speed-up in supervised machine learning,
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Old Rules in a New Game: Mapping Uncertainty Quantification to Quantum Machine Learning
Classical uncertainty quantification methods transfer to quantum machine learning; Bayesian quantum models and Gaussian dropout give the best-calibrated uncertainty estimates in small simulated experiments.