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 ...
A study in the Journal of Cosmology and Astroparticle Physics explores how a machine-learning strategy known as transfer learning could dramatically reduce the computational cost of searching for new ...
The numerical simulation of physical models is prevalent in science and engineering. These models mathematically represent a physical system, typically by partial differential equations (PDEs) or a ...
Two pioneers of artificial intelligence—John Hopfield and Geoffrey Hinton—won the Nobel Prize in physics Tuesday for helping create the building blocks of machine learning that is revolutionizing the ...
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 ...
As scientific instruments and the literature generate ever larger volumes of data, machine learning (ML) has become essential for organizing, analyzing and interpreting complex information. This ...
AI has started to emerge as one of the most effective technologies being used in cosmology lately. The power of machine ...
image of Winners of the 2024 Nobel Prize in Physics, John J. Hopfield (left) and Geoffrey E. Hinton. Winners of the 2024 Nobel Prize in Physics, John J. Hopfield (left) and Geoffrey E. Hinton. Credit: ...
In developing drugs using a platform that joins physics with machine learning, Schrödinger sees more than a passing resemblance to the studio whose Toy Story and other computer-generated movies ...
Hurricanes, or tropical cyclones, can be devastating natural disasters, leveling entire cities and claiming hundreds or thousands of lives. A key aspect of their destructive potential is their ...
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