Outubro 2023 vol. 10 num. 5 - IX Simpósio Internacional de Inovação e Tecnologia

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RECURRENT QUANTUM NEURAL NETWORKS: A REVIEW

RECURRENT QUANTUM NEURAL NETWORKS: A REVIEW

Jesus, Gleydson Fernandes de ; Silva, Valéria Loureiro da ;

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The analysis of historical data allows the execution of predictive tasks such as weather and stock price forecasting. To achieve these goals, Recurrent Neural Networks are implemented in classical computers and, in recent years, quantum methods have also emerged to perform prediction tasks based on the analysis of historical series, which have been called Quantum Recurrent Neural Network (QRNN). The objective of this work is to identify and review the main QRNNs discussed in the literature. A literature search in google scholar resulted in eight relevant papers that were reviewed. In general, the QRNNs show better training accuracy and stability compared to classical methods. It is not possible to speak of a training time advantage with the noisy and low-scale quantum computers currently available.

Full article:

The analysis of historical data allows the execution of predictive tasks such as weather and stock price forecasting. To achieve these goals, Recurrent Neural Networks are implemented in classical computers and, in recent years, quantum methods have also emerged to perform prediction tasks based on the analysis of historical series, which have been called Quantum Recurrent Neural Network (QRNN). The objective of this work is to identify and review the main QRNNs discussed in the literature. A literature search in google scholar resulted in eight relevant papers that were reviewed. In general, the QRNNs show better training accuracy and stability compared to classical methods. It is not possible to speak of a training time advantage with the noisy and low-scale quantum computers currently available.

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Palavras-chave: Quantum Computing; RNN; LSTM,

Palavras-chave: Quantum Computing; RNN; LSTM,

DOI: 10.5151/siintec2023-306159

Referências bibliográficas
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Como citar:

Jesus, Gleydson Fernandes de; Silva, Valéria Loureiro da; "RECURRENT QUANTUM NEURAL NETWORKS: A REVIEW", p. 357-365 . In: . São Paulo: Blucher, 2023.
ISSN 2357-7592, DOI 10.5151/siintec2023-306159

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