Unlabelled Data Improves Bayesian Uncertainty Calibration under Covariate Shift

ICML 2020 Alex J. ChanAhmed M. AlaaZhaozhi QianMihaela van der Schaar

Modern neural networks have proven to be powerful function approximators, providing state-of-the-art performance in a multitude of applications. They however fall short in their ability to quantify confidence in their predictions - this is crucial in high-stakes applications that involve critical decision-making... (read more)

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