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 ...

Researchers have developed a new tool, bimodularity, that adds directionality to community detection in networks.

Scientists in Spain have used genetic algorithms to optimize a feedforward artificial neural network for the prediction of energy generation of PV systems. Genetic algorithms use “parents” and ...

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.

A neural network is a series of algorithms that seek to identify relationships in a data set via a process that mimics how the human brain works.

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.