Are you a scientist with interesting yet unexplained data that you don’t have the time to analyse? You might want to get in touch with two physicist in the US who have created an algorithm that can ...

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 ...

NTT Research and Cornell Scientists Introduce Deep Physical Neural Networks Article in Nature Explains the Application of Physics-Aware Training Algorithm and Shares Results of Tests on Three Physical ...

The software tool developed by Stony Brook University uses self-supervised learning to detect long-term solar equipment damage weeks or years before manual inspections find it.

A new theoretical framework argues that the long-standing split between computational functionalism and biological naturalism misses how real brains actually compute.

Synthesis using physical modeling has a long history. As computational costs for physical modeling synthesis are often much greater than for conventional synthesis methods, most techniques currently ...