On Residual Networks Learning a Perturbation from Identity

11 Feb 2019Michael Hauser

The purpose of this work is to test and study the hypothesis that residual networks are learning a perturbation from identity. Residual networks are enormously important deep learning models, with many theories attempting to explain how they function; learning a perturbation from identity is one such theory... (read more)

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