← Search

Sarah Michalak

1 accepted papers

2019

On Mixup Training: Improved Calibration and Predictive Uncertainty for Deep Neural Networks

NeurIPS 2019poster

Mixup~\cite{zhang2017mixup} is a recently proposed method for training deep neural networks where additional samples are generated during training by convexly combining random pairs of images and their associated labels. While simple to implement, it has shown to be a surprisingly effective meth…