Enhancing Deep Learning with Bayesian Inference

Chapter 4 Introducing Bayesian Deep Learning

In Chapter 2, Fundamentals of Bayesian Inference, Fundamentals of Bayesian Inference, we saw how traditional methods for Bayesian inference can be used to produce model uncertainty estimates, and we introduced the properties of well-calibrated and well-principled methods for uncertainty estimation. While these traditional methods are powerful in many applications, Chapter 2, Fundamentals of Bayesian Inference also highlighted some of their limitations with respect to scaling. In Chapter 3, Fundamentals of Deep Learning, we saw the impressive things DNNs are capable of given large amounts of data; but we also learned that they aren’t perfect. In particular, they often lack robustness for out-of-distribution ...