Learning in Convolutional Neural Networks Accelerated by Integrating Transfer Entropy

Integrating transfer entropy (TE) feedback connections into the training process of convolutional neural networks (CNNs) can accelerate the training process and improve the classification accuracy, at the cost of increased computational overhead.