Trainability of Dissipative Perceptron-Based Quantum Neural Networks

Several architectures have been proposed for quantum neural networks (QNNs), with the goal of efficiently performing machine learning tasks on quantum data. Rigorous scaling results are urgently needed for specific QNN constructions to understand which, if any, will be trainable at a large scale. He...

Celý popis

Podrobná bibliografia

Vydané v:	Physical review letters Ročník 128; číslo 18; s. 180505
Hlavní autori:	Sharma, Kunal, Cerezo, M., Cincio, Lukasz, Coles, Patrick J.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States American Physical Society (APS) 06.05.2022
Predmet:	artificial neural networks CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS machine learning quantum algorithms quantum computation quantum information processing quantum networks
ISSN:	0031-9007, 1079-7114, 1079-7114
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!