The edge of chaos: quantum field theory and deep neural networks

27 September 2021

Papers citing "The edge of chaos: quantum field theory and deep neural networks"

7 / 7 papers shown

Title
Bayesian RG Flow in Neural Network Field Theories Jessica N. Howard Marc S. Klinger Anindita Maiti A. G. Stapleton 60 1 0 27 May 2024
Criticality versus uniformity in deep neural networks A. Bukva Jurriaan de Gier Kevin T. Grosvenor R. Jefferson K. Schalm Eliot Schwander 13 3 0 10 Apr 2023
Renormalization in the neural network-quantum field theory correspondence Harold Erbin Vincent Lahoche D. O. Samary 24 7 0 22 Dec 2022
Contrasting random and learned features in deep Bayesian linear regression Jacob A. Zavatone-Veth William L. Tong C. Pehlevan BDL MLT 20 26 0 01 Mar 2022
Unified field theoretical approach to deep and recurrent neuronal networks Kai Segadlo Bastian Epping Alexander van Meegen David Dahmen Michael Krämer M. Helias AI4CE BDL 20 20 0 10 Dec 2021
Towards quantifying information flows: relative entropy in deep neural networks and the renormalization group J. Erdmenger Kevin T. Grosvenor R. Jefferson 46 17 0 14 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 220 348 0 14 Jun 2018