Perceptron at Initialisation

In this notebook I study deep non-linear networks at initialisation. This is a prerequisite to understand such a network at the end of training, as is discussed in The Principles of Deep Learning Theory (PDLT) by Roberts, Yaida, and Hanin. This notebook also serves as a demonstration of my DeepLearningTheoryTools paclet for Mathematica and is meant to be read as complementary material to the PDLT book.