398 citations · 474 across the 13 of their papers we have counts for
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quant-ph2018
Efficiently measuring a quantum device using machine learning
D. T. Lennon, H. Moon, L. C. Camenzind +6
Scalable quantum technologies will present challenges for characterizing and tuning quantum devices. This is a time-consuming activity, and as the size of quantum systems increases…
quant-ph2018
Quantum algorithms for training Gaussian Processes
Zhikuan Zhao, Jack K. Fitzsimons, Michael A. Osborne +2
Gaussian processes (GPs) are important models in supervised machine learning. Training in Gaussian processes refers to selecting the covariance functions and the associated paramet…