3.3k citations · 5.6k across the 24 of their papers we have counts for
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Resource frugal optimizer for quantum machine learning
Charles Moussa, Max Hunter Gordon, Michal Baczyk +3
Quantum-enhanced data science, also known as quantum machine learning (QML), is of growing interest as an application of near-term quantum computers. Variational QML algorithms hav…
On the practical usefulness of the Hardware Efficient Ansatz
Lorenzo Leone, Salvatore F. E. Oliviero, Lukasz Cincio +1
Variational Quantum Algorithms (VQAs) and Quantum Machine Learning (QML) models train a parametrized quantum circuit to solve a given learning task. The success of these algorithms…
Quantum Algorithms for Geologic Fracture Networks
Jessie M. Henderson, Marianna Podzorova, M. Cerezo +4
Solving large systems of equations is a challenge for modeling natural phenomena, such as simulating subsurface flow. To avoid systems that are intractable on current computers, it…
A Hierarchy of Multipartite Correlations Based on Concentratable Entanglement
Louis Schatzki, Guangkuo Liu, M. Cerezo +1
Multipartite entanglement is one of the hallmarks of quantum mechanics and is central to quantum information processing. In this work we show that Concentratable Entanglement (CE),…
Exponential concentration in quantum kernel methods
Supanut Thanasilp, Samson Wang, M. Cerezo +1
Kernel methods in Quantum Machine Learning (QML) have recently gained significant attention as a potential candidate for achieving a quantum advantage in data analysis. Among other…