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 ...

Machine learning, and more generally, artificial intelligence, has achieved dramatic success over the past decade. This has been apparent in the tackling of notoriously challenging problems such as ...

Researchers at the University of Tokyo have identified a precise sweet spot where quantum reservoir computing, a machine learning approach that treats quantum systems as computational engines, reaches ...

Reservoir computing is a promising machine learning-based approach for the analysis of data that changes over time, such as ...

Neural networks revolutionized machine learning for classical computers: self-driving cars, language translation and even artificial intelligence software were all made possible. It is no wonder, then ...

"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 ...

Quantum computing appears on track to help companies in three main areas: optimization, simulation and machine learning. The appeal of quantum machine learning lies in its potential to tackle problems ...

Long confined to theoretical labs and sci-fi thrillers, quantum computing is fast emerging as a real-world technology with ...

As quantum computing advances, the conversation around post-quantum risk is moving from theoretical to practical. This shift is being driven by the reality ...

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