Evaluating Scalable Bayesian Deep Learning Methods for Robust Computer Vision

摘要

While deep neural networks have become the go-to approach in computer vision, the vast majority of these models fail to properly capture the uncertainty inherent in their predictions. Estimating this predictive uncertainty can be crucial, for example in a