Generalized Shape Metrics on Neural Representations. (arXiv:2110.14739v2 [stat.ML] UPDATED)

Understanding the operation of biological and artificial networks remains a
difficult and important challenge. To identify general principles, researchers
are increasingly interested in surveying large collections of networks that are
trained on, or biologically adapted to, similar tasks. A standardized set of
analysis tools is now needed to identify how network-level covariates -- such
as architecture, anatomical brain region, and model organism -- impact neural
representations (hidden layer activations). Here, we provide a rigorous
foundation for these analyses by defining …

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