The TLE-PINN method integrates EPINN and deep learning models through a transfer learning framework, combining strong physical constraints and efficient computational capabilities to accurately ...

STOCKHOLM — John Hopfield and Geoffrey Hinton were awarded the Nobel Prize in physics Tuesday for discoveries and inventions that formed the building blocks of machine learning. "This year's two Nobel ...

As artificial intelligence explodes in popularity, two of its pioneers have nabbed the 2024 Nobel Prize in physics. The prize surprised many, as these developments are typically associated with ...

Scientists have begun applying machine learning tools to nuclear physics challenges. In the past few years, a flurry of machine learning projects has come online in nuclear physics, and researchers ...

A new review in Nature chronicles the many ways machine learning is popping up in particle physics research. Experiments at the Large Hadron Collider produce about a million gigabytes of data every ...

Alfredo has a PhD in Astrophysics and a Master's in Quantum Fields and Fundamental Forces from Imperial College London.View full profile Alfredo has a PhD in Astrophysics and a Master's in Quantum ...

The groundwork for machine learning was laid down in the middle of last century. But increasingly powerful computers – harnessed to algorithms refined over the past decade – are driving an explosion ...

Parts of the brain not traditionally associated with learning science become active when people are confronted with solving physics problems, a new study shows. The researchers, led by Eric Brewe, PhD ...

Laurent Simons, a 15-year-old Belgian, has earned a PhD in quantum physics. He previously completed his bachelor's degree at ...

There is a shortage of medical physicists in Asia and the Pacific, yet demand for their crucial expertise is growing; these specialists play an important role in the safe and effective use of ...