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 ...

Read more about Quantum machine learning shows promise for adaptive learning, but classrooms are not ready on Devdiscourse ...

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 ...

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 ...

Researchers from the group of theoretical physicist Hans Briegel have collaborated with NVIDIA to develop an AI method that ...

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 ...

Organizations can start leveraging quantum-inspired techniques today to capture meaningful benefits without waiting for the ...

MicroAlgo QAS, by optimizing quantum circuit architectures, can significantly enhance the robustness of VQA in various noisy environments. By automatically searching for suitable circuit designs, QAS ...

What do cars, bridges and airplanes have in common? They are all exposed to the open air most of the time and are subjected to the sun’s ultraviolet (UV) radiation. Airplanes are particularly ...