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A Unified Framework for the Mechanics of Information in Convolutional Neural Network Image Space
This paper introduces a unified mathematical framework for modeling information propagation through convolutional neural networks (CNNs), with the aim of connecting descriptions of physical space and information space. A correspondence is presented linking discrete filter symmetry and the relativi
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