Optimal Tuning of Quantum Generative Adversarial Networks for Multivariate Distribution Loading

Optimal Tuning of Quantum Generative Adversarial Networks for Multivariate Distribution Loading

Loading data efficiently from classical memories to quantum computers is a key challenge of noisy intermediate-scale quantum computers. Such a problem can be addressed through quantum generative adversarial networks (qGANs), which are noise tolerant and agnostic with respect to data. Tuning a qGAN t...

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Bibliographic Details
Main Authors: Gabriele Agliardi, Enrico Prati
Format: Article
Language:English
Published: MDPI AG 2022-02-01
Series:Quantum Reports
Subjects:
quantum machine learning
quantum generative adversarial networks
multivariate quantum distributions
quantum data loading
quantum data encoding
quantum finance
Online Access:https://www.mdpi.com/2624-960X/4/1/6

Internet

https://www.mdpi.com/2624-960X/4/1/6

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