"Machine Learning in Quantum Sciences", outcome of a collaborative effort from world-leading experts, offers both an introduction to machine learning and deep neural networks, and an overview of their ...

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 ...

In a new study published in Physical Review Letters, researchers used machine learning to discover multiple new classes of ...

US scientist John Hopfield and British-Canadian researcher Geoffrey Hinton have won the Nobel Prize in Physics for creating the "building blocks of machine learning," the Royal Swedish Academy of ...

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 ...

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 ...

John Hopfield and Geoffrey Hinton were awarded the 2024 Nobel Prize in physics on Tuesday for their contributions to machine learning. Their research, which draws from statistical physics, helped ...

The quantum tangent kernel method is a mathematical approach used to understand how fast and how well quantum neural networks can learn. A quantum neural network is a machine learning model that runs ...

The computational demands of today’s AI systems are starting to outpace what classical hardware can deliver. How can we fix this? One possible solution is quantum machine learning (QML). QML ...

Orbital-free approach enables precise, stable, and physically meaningful calculation of molecular energies and electron ...