On the infinite width limit of neural networks with a standard
parameterization

On the infinite width limit of neural networks with a standard parameterization

21 January 2020

Jascha Narain Sohl-Dickstein

Papers citing "On the infinite width limit of neural networks with a standard parameterization"

11 / 11 papers shown

Title
Universal Sharpness Dynamics in Neural Network Training: Fixed Point Analysis, Edge of Stability, and Route to Chaos Dayal Singh Kalra Tianyu He M. Barkeshli 47 4 0 17 Feb 2025
The Optimization Landscape of SGD Across the Feature Learning Strength Alexander B. Atanasov Alexandru Meterez James B. Simon C. Pehlevan 43 2 0 06 Oct 2024
Connecting NTK and NNGP: A Unified Theoretical Framework for Wide Neural Network Learning Dynamics Yehonatan Avidan Qianyi Li H. Sompolinsky 60 8 0 08 Sep 2023
Controlled Descent Training Viktor Andersson B. Varga Vincent Szolnoky Andreas Syrén Rebecka Jörnsten Balázs Kulcsár 33 1 0 16 Mar 2023
The Geometry of Neural Nets' Parameter Spaces Under Reparametrization Agustinus Kristiadi Felix Dangel Philipp Hennig 22 11 0 14 Feb 2023
Catapult Dynamics and Phase Transitions in Quadratic Nets David Meltzer Junyu Liu 20 9 0 18 Jan 2023
Analytic theory for the dynamics of wide quantum neural networks Junyu Liu K. Najafi Kunal Sharma F. Tacchino Liang Jiang Antonio Mezzacapo 22 52 0 30 Mar 2022
Dataset Distillation with Infinitely Wide Convolutional Networks Timothy Nguyen Roman Novak Lechao Xiao Jaehoon Lee DD 24 229 0 27 Jul 2021
A Neural Tangent Kernel Perspective of GANs Jean-Yves Franceschi Emmanuel de Bézenac Ibrahim Ayed Mickaël Chen Sylvain Lamprier Patrick Gallinari 29 26 0 10 Jun 2021
Dataset Meta-Learning from Kernel Ridge-Regression Timothy Nguyen Zhourung Chen Jaehoon Lee DD 19 238 0 30 Oct 2020
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