Neural Networks as Kernel Learners: The Silent Alignment Effect

29 October 2021

Papers citing "Neural Networks as Kernel Learners: The Silent Alignment Effect"

7 / 57 papers shown

Title
A Framework and Benchmark for Deep Batch Active Learning for Regression David Holzmüller Viktor Zaverkin Johannes Kastner Ingo Steinwart UQCV BDL GP 23 34 0 17 Mar 2022
Tight Convergence Rate Bounds for Optimization Under Power Law Spectral Conditions Maksim Velikanov Dmitry Yarotsky 4 6 0 02 Feb 2022
Separation of Scales and a Thermodynamic Description of Feature Learning in Some CNNs Inbar Seroussi Gadi Naveh Z. Ringel 30 49 0 31 Dec 2021
Depth induces scale-averaging in overparameterized linear Bayesian neural networks Jacob A. Zavatone-Veth C. Pehlevan BDL UQCV MDE 36 8 0 23 Nov 2021
A Theory of Neural Tangent Kernel Alignment and Its Influence on Training H. Shan Blake Bordelon 11 11 0 29 May 2021
Properties of the After Kernel Philip M. Long 11 29 0 21 May 2021
Spectrum Dependent Learning Curves in Kernel Regression and Wide Neural Networks Blake Bordelon Abdulkadir Canatar C. Pehlevan 136 201 0 07 Feb 2020