A new technical paper titled “Exploring Neuromorphic Computing Based on Spiking Neural Networks: Algorithms to Hardware” was published by researchers at Purdue University, Pennsylvania State ...

Researchers have developed an algorithm to train an analog neural network just as accurately as a digital one, enabling the development of more efficient alternatives to power-hungry deep learning ...

Artificial Neural Networks: Learning by Doing Designed to mimic the brain itself, artificial neural networks use mathematical equations to identify and predict patterns in datasets and images.

The standard “back-propagation” training technique for deep neural networks requires matrix multiplication, an ideal workload for GPUs. With SLIDE, Shrivastava, Chen and Medini turned neural network ...

Feedforward neural networks (FNNs): A descendent of recurrent neural networks, FNN’s do not use any type of cycle or loop to process data and develop a model.

A review of what Google's Neural Matching Algorithm might be and how it might impact SEO.