An end-to-end trainable hybrid classical-quantum classifier

We introduce a hybrid model combining a quantum-inspired tensor network and a variational quantum circuit to perform supervised learning tasks. This architecture allows for the classical and quantum parts of the model to be trained simultaneously, providing an end-to-end training framework. We show...

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Veröffentlicht in:	Machine learning: science and technology 2021-12, Vol.2 (4), p.45021
Hauptverfasser:	Chen, Samuel Yen-Chi, Huang, Chih-Min, Hsing, Chia-Wei, Kao, Ying-Jer
Format:	Artikel
Sprache:	eng
Schlagworte:	Circuits Cognitive tasks Feature extraction Mathematical analysis MATHEMATICS AND COMPUTING principal component analysis Principal components analysis quantum machine learning tensor network Tensors variational quantum circuit
Online-Zugang:	Volltext
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