A study in the Journal of Cosmology and Astroparticle Physics explores how a machine-learning strategy known as transfer ...

Combining concepts from statistical physics with machine learning, researchers at the University of Bayreuth have shown that highly accurate and efficient predictions can now be made as to whether a ...

Space weather forecasting remains a major challenge in heliophysics, as geomagnetic storms continue to pose significant risks to satellite operations, power ...

Studying physics can be very useful—even when it comes to machine learning. A digital "super-brain" with built-in knowledge ...

Designing materials that steer light is a slow kind of trial and error. Each candidate structure must be tested in computer ...

Researchers employ machine learning to more accurately model the boundary layer wind field of tropical cyclones. Conventional approaches to storm forecasting involve large numerical simulations run on ...

Recent developments in machine learning techniques have been supported by the continuous increase in availability of high-performance computational resources and data. While large volumes of data are ...