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Quantum classical hybrid neural networks for continuous variable prediction

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  • Prateek Jain
  • Alberto Garcia Garcia

Abstract

Within this decade, quantum computers are predicted to outperform conventional computers in terms of processing power and have a disruptive effect on a variety of business sectors. It is predicted that the financial sector would be one of the first to benefit from quantum computing both in the short and long terms. In this research work we use Hybrid Quantum Neural networks to present a quantum machine learning approach for Continuous variable prediction.

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  • Prateek Jain & Alberto Garcia Garcia, 2022. "Quantum classical hybrid neural networks for continuous variable prediction," Papers 2212.04209, arXiv.org, revised Mar 2023.
    • Handle: RePEc:arx:papers:2212.04209
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    References listed on IDEAS

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    1. Gopala K. Anumanchipalli & Josh Chartier & Edward F. Chang, 2019. "Speech synthesis from neural decoding of spoken sentences," Nature, Nature, vol. 568(7753), pages 493-498, April.
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