2016
Exponential expressivity in deep neural networks through transient chaos
NeurIPS 2016poster
We combine Riemannian geometry with the mean field theory of high dimensional chaos to study the nature of signal propagation in deep neural networks with random weights. Our results reveal a phase transition in the expressivity of random deep networks, with networks in the chaotic phase computing n…