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On the Sample Complexity of Quantum Boltzmann Machine Learning
Luuk Coopmans, Marcello Benedetti
Quantum Boltzmann machines (QBMs) are machine-learning models for both classical and quantum data. We give an operational definition of QBM learning in terms of the difference in e…
Training Quantum Boltzmann Machines with the -Variational Quantum Eigensolver
Onno Huijgen, Luuk Coopmans, Peyman Najafi +2
The quantum Boltzmann machine (QBM) is a generative machine learning model for both classical data and quantum states. Training the QBM consists of minimizing the relative entropy…
Realization of quantum signal processing on a noisy quantum computer
Yuta Kikuchi, Conor Mc Keever, Luuk Coopmans +2
Quantum signal processing (QSP) is a powerful toolbox for the design of quantum algorithms and can lead to asymptotically optimal computational costs. Its realization on noisy quan…