Machine learning is becoming an essential part of a physicist’s toolkit. How should new students learn to use it? When Radha Mastandrea started her undergraduate physics program at MIT in 2015, she ...

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

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

Scientists found that transfer learning can make the search for new physics in the universe much faster, slashing the need ...

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 ...

Researchers in Sweden have developed a machine-learning approach that embeds the laws of physics directly into neural ...

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 ...

See more of our trusted coverage when you search. Prefer Newsweek on Google to see more of our trusted coverage when you search. John Hopfield and Geoffrey Hinton were awarded the 2024 Nobel Prize in ...

Two scientists have been awarded the Nobel Prize in Physics "for foundational discoveries and inventions that enable machine learning with artificial neural networks." John Hopfield, an emeritus ...

Researchers at the University of California San Diego and the Allen Institute for AI have built a climate emulator that ...

AI has started to emerge as one of the most effective technologies being used in cosmology lately. The power of machine ...