Neural entropy enhanced machine learning

A computing device, comprising:

• a processor;
• a memory, the memory comprising instructions, which when executed by the processor, cause the processor to perform operations comprising:
• obtaining a deep neural network (DNN) with a training dataset;
• determining a spreading signal between neurons in multiple adjacent layers of the DNN wherein the spreading signal is an element-wise multiplication of input activations between the neurons in a first layer to neurons in a second next layer with a corresponding weight matrix of connections between such neurons;
• and
• determining neural entropies of respective connections between neurons by calculating an exponent of a volume of an area covered by the spreading signal.

A machine readable medium having instructions which when executed by a processor, cause the processor to perform operations comprising:

• obtaining a deep neural network (DNN) with a training dataset;
• determining a spreading signal between neurons in multiple adjacent layers of the DNN wherein the spreading signal is an element-wise multiplication of input activations between the neurons in a first layer to neurons in a second next layer with a corresponding weight matrix of connections between such neurons;
• and
• determining neural entropies of respective connections between neurons by calculating an exponent of a volume of an area covered by the spreading signal.