c3177be226ee12e34d6ba3b5e6fe6a5b-Paper-Conference.pdf

This paper questions the effectiveness of a modern predictive uncertainty quantification approach, called evidential deep learning (EDL), in which a single neural network model is trained to learn a meta distribution over the predictive distribution by minimizing a specific objective function.