Importance

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Abstract

Performance of a neural network is usually a function of the capacity, or complexity, of the neural network, including the depth of the neural network (i.e. the number of layers in the neural network) and/or the width of the neural network (i.e. the number of hidden channels). However, improving performance of a neural network by simply increasing its capacity has drawbacks, the most notable being the increased computational cost of a higher-capacity neural network. Since modern neural networks are configured such that the same neural network is evaluated regardless of the input, a higher capacity neural network means a higher computational cost incurred per input processed. The present disclosure provides for a multi-layer neural network that allows for dynamic path selection through the neural network when processing an input, which in turn can allow for increased neural network capacity without incurring the typical increased computation cost associated therewith.

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First Claim