Quantum Advantage Seeker with Kernels (QuASK): a software framework to speed up the research in quantum machine learning

30 June 2022

Papers citing "Quantum Advantage Seeker with Kernels (QuASK): a software framework to speed up the research in quantum machine learning"

9 / 9 papers shown

Title
Quantum Kernel Methods under Scrutiny: A Benchmarking Study Jan Schnabel M. Roth 62 3 0 06 Sep 2024
A novel feature selection method based on quantum support vector machine Haiyan Wang 16 9 0 29 Nov 2023
sQUlearn -- A Python Library for Quantum Machine Learning D. Kreplin Moritz Willmann Jan Schnabel Frederic Rapp Manuel Hagelüken M. Roth GP 30 9 0 15 Nov 2023
Unravelling physics beyond the standard model with classical and quantum anomaly detection Julian Schuhmacher Laura Boggia Vasilis Belis E. Puljak Michele Grossi M. Pierini S. Vallecorsa F. Tacchino Panagiotis Kl Barkoutsos I. Tavernelli 16 26 0 25 Jan 2023
Quantum Machine Learning Applied to the Classification of Diabetes Juan Kenyhy Hancco-Quispe Jordan Piero Borda-Colque Fred Torres-Cruz 11 5 0 31 Dec 2022
Parameterized Quantum Circuits with Quantum Kernels for Machine Learning: A Hybrid Quantum-Classical Approach Daniel T. Chang 25 4 0 28 Sep 2022
Automatic and effective discovery of quantum kernels Massimiliano Incudini Daniele Lizzio Bosco F. Martini Michele Grossi Giuseppe Serra Alessandra Di Pierro 31 4 0 22 Sep 2022
Connecting ansatz expressibility to gradient magnitudes and barren plateaus Zoë Holmes Kunal Sharma M. Cerezo Patrick J. Coles 143 423 0 06 Jan 2021
Noise-Induced Barren Plateaus in Variational Quantum Algorithms Samson Wang Enrico Fontana M. Cerezo Kunal Sharma A. Sone L. Cincio Patrick J. Coles 138 655 0 28 Jul 2020