5 papers
Entanglement is Half the Story: Post-Selection vs. Partial Traces
Gustav J L Jäger, Krzysztof Bieniasz, Martin B Plenio +1
While tensor networks have their traditional application in simulating quantum systems, in the recent decade they have gathered interest as machine learning models. We combine the…
Theory and interpretability of Quantum Extreme Learning Machines: a Pauli-transfer matrix approach
Markus Gross, Hans-Martin Rieser
Quantum reservoir computers (QRCs) have emerged as a promising approach to quantum machine learning, since they utilize the natural dynamics of quantum systems for data processing…
Kernel-based optimization of measurement operators for quantum reservoir computers
Markus Gross, Hans-Martin Rieser
Finding optimal measurement operators is crucial for the performance of quantum reservoir computers (QRCs), since they employ a fixed quantum feature map. We formulate the training…
A Hybrid Quantum Solver for Gaussian Process Regression
Kerem Bükrü, Steffen Leger, M. Lautaro Hickmann +3
Gaussian processes are widely known for their ability to provide probabilistic predictions in supervised machine learning models. Their non-parametric nature and flexibility make t…
Hybrid quantum tensor networks for aeroelastic applications
M. Lautaro Hickmann, Pedro Alves, David Quero +2
We investigate the application of hybrid quantum tensor networks to aeroelastic problems, harnessing the power of Quantum Machine Learning (QML). By combining tensor networks with…