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 ...

Artificial intelligence (AI) has become integral to our daily lives, from virtual assistants like Siri to personalized recommendations on Netflix. As AI technology advances, quantum machine learning ...

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

"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 ...

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 ...

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

Quantum Machine Learning is an interdisciplinary field that harnesses the computational power of quantum systems to develop algorithms that can process and analyze data more efficiently than classical ...

Surpasses $3.5 Billion in Assets and Earns 5-Star Morningstar Rating Defiance ETFs today announced that its Quantum Computing ETF (QTUM) has surpassed $3.5 billion in assets under management and has ...

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 ...

In a new study published in Physical Review Letters, researchers used machine learning to discover multiple new classes of two-dimensional memories, systems that can reliably store information despite ...

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