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Explananda and explanantia in deep neural network models of neurological network functions
Published online by Cambridge University Press: 06 December 2023
Abstract
Depending on what we mean by “explanation,” challenges to the explanatory depth and reach of deep neural network models of visual and other forms of intelligent behavior may need revisions to both the elementary building blocks of neural nets (the explananda) and to the ways in which experimental environments and training protocols are engineered (the explanantia). The two paths assume and imply sharply different conceptions of how an explanation explains and of the explanatory function of models.
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- Copyright © The Author(s), 2023. Published by Cambridge University Press
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Target article
Deep problems with neural network models of human vision
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Clarifying status of DNNs as models of human vision