Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning

Abstract

This paper introduces and evaluates the idea described in “Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning”, and reports empirical results that helped shape subsequent work in uncertainty, bayesian.