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 ...

By combining physics-based methods with machine learning, a team at the Institute of Thermodynamics and Sustainable ...

This Collection supports and amplifies research related to SDG3, SDG9 and SDG10. Physics-Informed Machine Learning (PI-ML) combines principles from physics- and biology-based modeling with data-driven ...

For more than 20 years in experimental particle physics and astrophysics, machine learning has been accelerating the pace of science, helping scientists tackle problems of greater and greater ...

The Royal Swedish Academy of Sciences has announced that the Nobel Prize in Physics will be awarded to Professor Emeritus The Royal Swedish Academy of Sciences stated, 'Professor Hopfield developed ...

A research team has studied the development of the Shanghai Typhoon Model from a traditional physics-based regional model toward a data-driven, machine-learning typhoon forecasting system. They ...

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 ...

Two pioneers in artificial intelligence, John Hopfield and Geoffrey Hinton, were awarded the Nobel Prize in Physics on Tuesday for their foundational contributions to machine learning, which is ...

John J Hopfield and Geoffrey E Hinton have won the Nobel Prize in Physics 2024 for their pivotal work in machine learning with artificial neural networks. Their innovations allow computers to mimic ...