Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide Neural Networks

19 May 2022

Papers citing "Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide Neural Networks"

11 / 61 papers shown

Title
The Onset of Variance-Limited Behavior for Networks in the Lazy and Rich Regimes Alexander B. Atanasov Blake Bordelon Sabarish Sainathan Cengiz Pehlevan 22 26 0 23 Dec 2022
Infinite-width limit of deep linear neural networks Lénaïc Chizat Maria Colombo Xavier Fernández-Real Alessio Figalli 31 14 0 29 Nov 2022
Meta-Principled Family of Hyperparameter Scaling Strategies Sho Yaida 58 16 0 10 Oct 2022
Second-order regression models exhibit progressive sharpening to the edge of stability Atish Agarwala Fabian Pedregosa Jeffrey Pennington 35 26 0 10 Oct 2022
The Influence of Learning Rule on Representation Dynamics in Wide Neural Networks Blake Bordelon Cengiz Pehlevan 41 22 0 05 Oct 2022
Decomposing neural networks as mappings of correlation functions Kirsten Fischer Alexandre René Christian Keup Moritz Layer David Dahmen M. Helias FAtt 14 14 0 10 Feb 2022
The Eigenlearning Framework: A Conservation Law Perspective on Kernel Regression and Wide Neural Networks James B. Simon Madeline Dickens Dhruva Karkada M. DeWeese 48 27 0 08 Oct 2021
The large learning rate phase of deep learning: the catapult mechanism Aitor Lewkowycz Yasaman Bahri Ethan Dyer Jascha Narain Sohl-Dickstein Guy Gur-Ari ODL 159 234 0 04 Mar 2020
Spectrum Dependent Learning Curves in Kernel Regression and Wide Neural Networks Blake Bordelon Abdulkadir Canatar Cengiz Pehlevan 144 201 0 07 Feb 2020
Why bigger is not always better: on finite and infinite neural networks Laurence Aitchison 175 51 0 17 Oct 2019
Trainability and Accuracy of Neural Networks: An Interacting Particle System Approach Grant M. Rotskoff Eric Vanden-Eijnden 59 118 0 02 May 2018