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Abstract

A method of initializing and training a neural network having a plurality of layers includes defining a first function configured to generate a filter based on a plurality of variance values associated with respective pairs of parameters of the plurality of layers, calculating the plurality of variance values based on depths of respective layers of the plurality of layers such that the variance values increase as the depths increase, calculating a covariance matrix using the first function, the covariance matrix having a block structure and each block of the covariance matrix corresponding to a covariance between a respective parameter and other parameters of the plurality of layers, providing, as input, the covariance matrix to the neural network to initialize the neural network for training, and generating, using the neural network, an output based on the covariance matrix.

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First Claim