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Wai Hoh Tang

2 accepted papers

2023

MixupE: Understanding and improving Mixup from directional derivative perspective

UAI 2023poster

Mixup is a popular data augmentation technique for training deep neural networks where additional samples are generated by linearly interpolating pairs of inputs and their labels. This technique is known to improve the generalization performance in many learning paradigms and applications. In this w…

2023

PICProp: Physics-Informed Confidence Propagation for Uncertainty Quantification

NeurIPS 2023poster

Standard approaches for uncertainty quantification in deep learning and physics-informed learning have persistent limitations. Indicatively, strong assumptions regarding the data likelihood are required, the performance highly depends on the selection of priors, and the posterior can be sampled onl…