By applying new methods of machine learning to quantum chemistry research, Heidelberg University scientists have made ...

Molecular machine learning (ML) underpins critical workflows in drug discovery, material science, and catalyst optimization by rapidly predicting molecular interactions and properties. For instance, ...

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 ...

The idea that quantum computing could transform medical artificial intelligence (AI) has gained momentum in recent years, driven by advances in cloud-accessible quantum platforms and hybrid computing ...

"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 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 ...

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 ...

D-Wave Quantum (NYSE:QBTS) agreed to acquire Quantum Circuits, Inc., aiming to combine annealing and gate-model quantum technologies. The company also signed a $10 million, two-year Quantum Computing ...

Orbital-free approach enables precise, stable, and physically meaningful calculation of molecular energies and electron densities By applying new methods of machine learning in quantum chemistry ...