Calibrating Deep Convolutional Gaussian Processes

26 May 2018Gia-Lac TranEdwin V. BonillaJohn P. CunninghamPietro MichiardiMaurizio Filippone

The wide adoption of Convolutional Neural Networks (CNNs) in applications where decision-making under uncertainty is fundamental, has brought a great deal of attention to the ability of these models to accurately quantify the uncertainty in their predictions. Previous work on combining CNNs with Gaussian processes (GPs) has been developed under the assumption that the predictive probabilities of these models are well-calibrated... (read more)

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