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 ...

In a Nature Communications study, researchers from China have developed an error-aware probabilistic update (EaPU) method ...

Physicists have devised an algorithm that provides a mathematical framework for how learning works in lattices called mechanical neural networks. It's easy to think that machine learning is a ...

Recently, a research team led by Prof. GAO Xiaoming from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, developed an intelligent neural network algorithm that effectively ...

The rise of artificial intelligence (AI) deep learning algorithms is helping to accelerate brain-computer interfaces (BCIs). Published in this month’s Nature Neuroscience is new research that shows ...

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 ...

In a nutshell: Deep Learning Super Sampling (DLSS) technology popularized the use of neural networks to upscale and enhance real-time 3D graphics, delivering significant improvements in both ...

Obtaining the gradient of what's known as the loss function is an essential step to establish the backpropagation algorithm developed by University of Michigan researchers to train a material. The ...