Towards quantifying information flows: relative entropy in deep neural networks and the renormalization group

14 July 2021

Papers citing "Towards quantifying information flows: relative entropy in deep neural networks and the renormalization group"

3 / 3 papers shown

Title
Bayesian RG Flow in Neural Network Field Theories Jessica N. Howard Marc S. Klinger Anindita Maiti A. G. Stapleton 50 1 0 27 May 2024
Entropic alternatives to initialization Daniele Musso 29 1 0 16 Jul 2021
Dynamical Isometry and a Mean Field Theory of CNNs: How to Train 10,000-Layer Vanilla Convolutional Neural Networks Lechao Xiao Yasaman Bahri Jascha Narain Sohl-Dickstein S. Schoenholz Jeffrey Pennington 220 330 0 14 Jun 2018