4 citations
3 papers
quant-ph2022
The effect of the processing and measurement operators on the expressive power of quantum models
Aikaterini, Gratsea, Patrick Huembeli
There is an increasing interest in Quantum Machine Learning (QML) models, how they work and for which applications they could be useful. There have been many different proposals on…
cond-mat.dis-nn2021★ 4 cited
Storage properties of a quantum perceptron
Aikaterini, Gratsea, Valentin Kasper +1
Driven by growing computational power and algorithmic developments, machine learning methods have become valuable tools for analyzing vast amounts of data. Simultaneously, the fast…
quant-ph2021★ 2 cited
Exploring Quantum Perceptron and Quantum Neural Network structures with a teacher-student scheme
Aikaterini, Gratsea, Patrick Huembeli
Near-term quantum devices can be used to build quantum machine learning models, such as quantum kernel methods and quantum neural networks (QNN) to perform classification tasks. Th…