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

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

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 ...

Scientists have begun turning to new tools offered by machine learning to help save time and money. In the past several years, nuclear physics has seen a flurry of machine learning projects come ...

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 ...

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

The Nobel Prize in Physics was awarded to US scientist John Hopfield and British-Canadian researcher Geoffrey Hinton for their work in the field of machine learning, the Royal Swedish Academy of ...

Mathematicians working on fluid dynamics, symbolic computation, and formal proof verification are finding that ...

Blood pressure is a key metric of cardiovascular health, but standard methods for measuring it rely on occasional readings ...

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 ...

Machine learning can get a boost from quantum physics. On certain types of machine learning tasks, quantum computers have an exponential advantage over standard computation, scientists report in the ...