Mattias Teye

Bayesian Uncertainty Estimation for Batch Normalized Deep Networks

We show that training a deep network using batch normalization is equivalent to approximate inference in Bayesian models. We further demonstrate that this finding allows us to make meaningful estimates of the model uncertainty using conventional architectures, without modifications to the network or…