Enhancing Deep Learning with Bayesian Inference

Chapter 2 Fundamentals of Bayesian Inference

Before we get into Bayesian inference with Deep Neural Networks (DNNs), we should take some time to understand the fundamentals. In this chapter, we’ll do just that: exploring the core concepts of Bayesian modeling, and taking a look at some of the popular methods used for Bayesian inference. By the end of this chapter, you should have a good understanding of why we use probabilistic modeling, and what kinds of properties we look for in well principled – or well conditioned – methods.

This content will be covered in the following sections:

• Refreshing our knowledge of Bayesian modeling

• Bayesian inference via sampling

• Exploring the Gaussian processes

2.1 Refreshing our knowledge of Bayesian modeling ...