Enhancing Deep Learning with Bayesian Inference

Chapter 7 Practical Considerations for Bayesian Deep Learning

Over the last two chapters, Chapter 5, Principled Approaches for Bayesian Deep Learning and Chapter 6, Using the Standard Toolbox for Bayesian Deep Learning, we’ve been introduced to a range of methods that facilitate Bayesian inference with neural networks. Chapter 5, Principled Approaches for Bayesian Deep Learning introduced specially crafted Bayesian neural network approximations, while Chapter 6, Using the Standard Toolbox for Bayesian Deep Learning showed how we can use the standard toolbox of machine learning to add uncertainty estimates to our models. These families of methods come with their own advantages and disadvantages. In this chapter, we will explore some of these ...