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 ...

Another theory held that the forces between two particles falls off exponentially in direct relationship to the distance between two particles and that the factor by which it drops is not dependent on ...

John Hopfield and Geoffrey Hinton won the Nobel Prize in Physics for their foundational work in artificial intelligence. Hinton, known as the godfather of AI, is a dual citizen of Canada and Britain, ...

The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle ...

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 Laureates ...

By applying new methods of machine learning to quantum chemistry research, Heidelberg University scientists have made significant strides in computational chemistry. They have achieved a major ...

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 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 ...

Don’t know your convolutional neural networks from your boosted decision trees? Symmetry is here to help. It’s time for some deep learning. Check out this list to pick up some new terminology—and ...

Muons tend to scatter more from high-atomic-number materials, so the technique is particularly sensitive to the presence of materials such as uranium. As a result, it has been used to create systems ...