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Uncertainty Calibration in Bayesian Neural Networks via Distance-Aware Priors
As we move away from the data, the predictive uncertainty should increase, since a great variety of explanations are consistent with the little available information.
Scalable Gaussian Processes for Characterizing Multidimensional Change Surfaces
We present a scalable Gaussian process model for identifying and characterizing smooth multidimensional changepoints, and automatically learning changes in expressive covariance structure.
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