Angelos Chatzimparmpas

Evaluating the Utility of Conformal Prediction Sets for AI-Advised Image Labeling

As deep neural networks are more commonly deployed in high-stakes domains, their black-box nature makes uncertainty quantification challenging. We investigate the effects of presenting conformal prediction sets---a distribution-free class of methods for generating prediction sets with specified coverage---to express u…