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 ...

When a bond is unavailable for an asset manager to buy, perhaps due to liquidity constraints, the manager may search for a substitute bond with similar features. Methods exist to help the manager find ...

Traditional machine learning methods suffer from the curse of dimensionality. Here, Ryan Samson, Jeffrey Berger, Luca Candelori, Vahagn Kirakosyan, Kharen Musaelian and Dario Villani introduce a novel ...

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 ...

When a quantum computer processes data, it must translate it into understandable quantum data. Algorithms that carry out this 'quantum compilation' typically optimize one target at a time. However, a ...

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 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 ...

About a year and a half ago, quantum control startup Quantum Machines and Nvidia announced a deep partnership that would bring together Nvidia’s DGX Quantum computing platform and Quantum Machine’s ...

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 ...