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Quantum machine learning in high energy physics
Abstract Machine learning has been used in high energy physics (HEP) for a long time,
primarily at the analysis level with supervised classification. Quantum computing was …
primarily at the analysis level with supervised classification. Quantum computing was …
Effect of data encoding on the expressive power of variational quantum-machine-learning models
Quantum computers can be used for supervised learning by treating parametrized quantum
circuits as models that map data inputs to predictions. While a lot of work has been done to …
circuits as models that map data inputs to predictions. While a lot of work has been done to …
Generalization in quantum machine learning: A quantum information standpoint
Quantum classification and hypothesis testing (state and channel discrimination) are two
tightly related subjects, the main difference being that the former is data driven: how to …
tightly related subjects, the main difference being that the former is data driven: how to …
Quantum machine learning for classical data
L Wossnig - arxiv preprint arxiv:2105.03684, 2021 - arxiv.org
In this dissertation, we study the intersection of quantum computing and supervised machine
learning algorithms, which means that we investigate quantum algorithms for supervised …
learning algorithms, which means that we investigate quantum algorithms for supervised …