Better depth-width trade-offs for neural networks through the lens of dynamical systems

Vaggos Chatziafratis, Sai Ganesh Nagarajan, Ioannis Panageas

Abstract: The expressivity of neural networks as a function of their depth, width and type of activation units has been an important question in deep learning theory. Recently, depth separation results for R...