29 citations · 44 across the 6 of their papers we have counts for
Showing 2023Show all
2 papers · 1 filter
quant-ph2023★ 3 cited
sQUlearn -- A Python Library for Quantum Machine Learning
David A. Kreplin, Moritz Willmann, Jan Schnabel +3
sQUlearn introduces a user-friendly, NISQ-ready Python library for quantum machine learning (QML), designed for seamless integration with classical machine learning tools like scik…
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…