May 25, 2025 · Quantum machine learning (QML) is a rapidly growing field that combines quantum computing principles with traditional machine learning. It seeks to revolutionize machine learning by …

Jul 12, 2021 · We now know that quantum computers have the potential to boost the performance of machine learning systems, and may eventually power efforts in fields from drug discovery to fraud …

Feb 1, 2024 · Even though results are promising, quantum machine learning is far from achieving its full potential. An improvement in quantum hardware is required for this potential to be achieved since the …

Nov 22, 2024 · We benchmarked ML-QEM using a variety of machine learning models—linear regression, random forest, multilayer perceptron and graph neural networks—on diverse classes of …

Jul 12, 2021 · The quantum algorithm, based on a quantum kernel method, employs a time-proven conventional machine learning model to learn the kernel function, which finds the relevant features in …

Feb 11, 2025 · Machine learning techniques are essential tools to compute efficient, yet accurate, force fields for atomistic simulations. This approach has recently been extended to incorporate quantum …

Mar 3, 2024 · We benchmark a variety of machine learning models---linear regression, random forests, multi-layer perceptrons, and graph neural networks---on diverse classes of quantum circuits, over …

Dec 4, 2025 · We’re inventing what’s next in quantum research. Explore our recent work, access unique toolkits, and discover the breadth of topics that matter to us.

Jun 4, 2024 · Quantum machine learning on near-term quantum devices: Current state of supervised and unsupervised techniques for real-world applications for Physical Review Applied by Yaswitha …

Aug 31, 2025 · Quantum Machine Learning for minimal omics datasets with large feature space using embeddings and feature selection techniques Abstract Despite the amount of omics data generated …