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    Article

    Theory of overparametrization in quantum neural networks

    The prospect of achieving quantum advantage with quantum neural networks (QNNs) is exciting. Understanding how QNN properties (for example, the number of parameters M) affect the loss landscape is crucial to desi...

    Martín Larocca, Nathan Ju, Diego García-Martín in Nature Computational Science (2023)

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    Challenges and opportunities in quantum machine learning

    At the intersection of machine learning and quantum computing, quantum machine learning has the potential of accelerating data analysis, especially for quantum data, with applications for quantum materials, bi...

    M. Cerezo, Guillaume Verdon, Hsin-Yuan Huang, Lukasz Cincio in Nature Computational Science (2022)

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    Seeking quantum advantage for neural networks

    A study based on effective dimension shows that a quantum neural network can have increased capability and trainability as compared to its classical counterpart.

    Patrick J. Coles in Nature Computational Science (2021)