Fast predictive uncertainty for classification with Bayesian deep networks

Marius Hobbhahn, Agustinus Kristiadi, Philipp Hennig

Abstract: In Bayesian Deep Learning, distributions over the output of classification neural networks are often approximated by first constructing a Gaussian distribution over the weights, then sampling from ...