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 ...

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

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 study published in Engineering introduces an innovative high-precision aerosol algorithm for geostationary meteorological satellite. Entitled “A Deep-Learning and Transfer-Learning Hybrid Aerosol ...

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 ...