Cost Functions and Style Transfer
Umberto Michelucci · Apress eBooks · 2019
In this chapter we will look in more depth at the role of the cost function in neural network models. In particular, we will discuss the MSE (mean square error) and the cross-entropy and discuss their origin and their interpretation. We will look at why we can use them to solve problems and how the MSE can be interpreted in a statistical sense, as well as how cross-entropy is related to information theory. Then, to give you an example of a much more advanced use of special loss functions, we will learn how to do neural style transfer, where we will discuss a neural network to paint in the style of famous painters.