ORNL researchers design novel method for energy-efficient deep neural networks

Researchers at DOE’s Oak Ridge National Laboratory (ORNL) have developed a novel method for more efficiently training large numbers of networks capable of solving complex science problems. Specifically, Mohammed Alawad, Hong-Jun Yoon, and Gina Tourassi of ORNL’s Computer Science and Engineering Division, have demonstrated that by converting deep learning neural networks (DNNs) to ‘deep spiking’ neural networks (DSNNs) they can improve the efficiency of network design and training.

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