SYSTEM AND METHOD FOR TRAINING ARTIFICIAL NEURAL NETWORKS AT DIFFERENT SCALES

Abstract

A computer system is configured to scale an artificial neural network (ANN), by performing the steps of: initializing a first ANN based at least on first parameters and a first number of neurons per layer; training the first ANN using training inputs to adjust weights and biases of the first ANN; upon determining that an accuracy of the first ANN at generating outputs is greater than a threshold value, generating a second number of neurons per layer that is scaled from the first number of neurons per layer; initializing a second ANN based at least on the first parameters and on the second number of neurons per layer; training the second ANN using training inputs to adjust weights and biases of the second ANN; and executing the second ANN to generate inferences based on inference data input thereto.

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