
MixupMP proposes a novel approach to uncertainty quantification in deep learning, outperforming existing methods.


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posterior-uncertainty-quantification-in-neural-networks-using-data-augmentation


Posterior Uncertainty Quantification in Neural Networks using Data Augmentation


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Deep learning models sometimes make overconfident but incorrect predictions, leading to serious consequences. Uncertainty quantification methods aim to estimate confidence beyond accuracy.


a-survey-on-uncertainty-quantification-for-deep-learning-an-uncertainty-source-s-perspective


A Survey on Uncertainty Quantification for Deep Learning: An Uncertainty Source’s Perspective
