Maximizing Overall Diversity for Improved Uncertainty Estimates in Deep Ensembles

18 Jun 2019Siddhartha JainGe LiuJonas MuellerDavid Gifford

The inaccuracy of neural network models on inputs that do not stem from the training data distribution is both problematic and at times unrecognized. Model uncertainty estimation can address this issue, where uncertainty estimates are often based on the variation in predictions produced by a diverse ensemble of models applied to the same input... (read more)

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