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quant-ph2023★ 23 cited
Reduction of finite sampling noise in quantum neural networks
David A. Kreplin, Marco Roth
Quantum neural networks (QNNs) use parameterized quantum circuits with data-dependent inputs and generate outputs through the evaluation of expectation values. Calculating these ex…
quant-ph2023★ 29 cited
Quantum Gaussian Process Regression for Bayesian Optimization
Frederic Rapp, Marco Roth
Gaussian process regression is a well-established Bayesian machine learning method. We propose a new approach to Gaussian process regression using quantum kernels based on paramete…