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It is often remarked that neural networks fail to increase their uncertainty when predicting on data far from the training distribution.
Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty
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Supervised Learning of Probability Distributions by Neural Networks
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Training Stochastic Model Recognition Algorithms as Networks can lead to Maximum Mutual Information Estimation of Parameters
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Sphere Packings, Lattices and Groups. , volume 96
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Using pre-training can improve model robustness and uncertainty
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