On Neural Network Kernels and the Storage Capacity Problem
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Updated: Sep 28, 2025

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
Published on: March 2, 2015
Jacob A Zavatone-Veth1, Cengiz Pehlevan2
1Department of Physics and Center for Brain Science, Harvard University, Cambridge, MA 02138, U.S.A. jzavatoneveth@g.harvard.edu.
Abstract:
In this short note, we reify the connection between work on the storage capacity problem in wide two-layer treelike neural networks and the rapidly growing body of literature on kernel limits of wide neural networks. Concretely, we observe that the "effective order parameter" studied in the statistical mechanics literature is exactly equivalent to the infinite-width neural network gaussian process kernel. This correspondence connects the expressivity and trainability of wide two-layer neural networks.
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