The strategic advantage of QML continues to expand its presence in industries that deal with complex, high-dimensional data.

Tacchino and co have created an algorithm that takes a classical vector (like an image) as an input, combines it with a quantum weighting vector, and then produces a 0 or 1 output.

This diagram illustrates how the team reduces quantum circuit complexity in machine learning using three encoding methods—variational, genetic, and matrix product state algorithms. All methods ...

Scientists say they have made a breakthrough after developing a quantum computing technique to run machine learning algorithms that outperform state-of-the-art classical computers. The researchers ...

shenzhen, May 20, 2025 (GLOBE NEWSWIRE) -- Shenzhen, May. 20, 2025/––MicroAlgo Inc. (the "Company" or "MicroAlgo") (NASDAQ: MLGO), announced that quantum algorithms will be deeply integrated ...

Researchers enhance quantum machine learning algorithms. ScienceDaily . Retrieved June 2, 2025 from www.sciencedaily.com / releases / 2021 / 03 / 210316112244.htm ...

Physicists in the US have used machine learning to determine the phase diagram of a system of 12 idealized quantum particles to a higher precision than ever before. The work was done by Eun-Ah Kim of ...

In quantum physics, there is an implicit understanding that the answers are often “probabilistic” Perhaps this is the key insight which can allow us to leverage the power of machine learning ...

Semiconductor processing is notoriously challenging. It is one of the most intricate feats of modern engineering due to the ...

Quantum computers coupled with traditional machine learning show clear benefits. John Timmer – Jun 9, 2022 2:00 pm | 67 Google's Sycamore processor.

Further research in quantum machine learning for data analysis is necessary before it can be of use to industries for practical application, Chen said, and an IUCRC would make tangible progress. “We ...