Transferred Discrepancy: Quantifying the Difference Between Representations

Understanding what information neural networks capture is an essential problem in deep learning, and studying whether different models capture similar features is an initial step to achieve this goal. Previous works sought to define metrics over the feature matrices to measure the difference between two models... (read more)

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