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Machine learning in the quantum era

  • Wissen – Quantum Computing
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Digitale Welt

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References

  • Aaronson, S. (2015). Read the fine print. Nature Physics 11.4, 291.

    Article  Google Scholar 

  • Benedetti, M., Realpe-Gómez, J., & Perdomo-Ortiz, A. (2018). Quantum-assisted helmholtz machines: a quantum–classical deep learning framework for industrial datasets in near-term devices. Quantum Science and Technology 3.3.

    Google Scholar 

  • Dunjko, V., & Briegel, H. J. (2018). Machine learning & artificial intelligence in the quantum domain: a review of recent progress. Reports on Progress in Physics 81.7.

    Google Scholar 

  • Fahri, E., & Neven, H. (2018). Classification with quantum neural networks on near term processors. arXiv preprint.

    Google Scholar 

  • Lopez-Chagoya, T. J. (2018). Hybrid Helmholtz machine: A gate-based quantum circuit implementation. Maastricht, The Netherlands: Maastricht University: Master’s thesis.

    Google Scholar 

  • MacKay, D. J. (2003). Information Theory, Inference, and Learning Algorithms. Cambridge University Press.

    Google Scholar 

  • QuTech. (2018). Quantum Inspire Home. Retrieved from Quantum Inspire: https://www.quantum-inspire.com/

  • Rebentrost, P., Bromley, T. R., Weedbrook, C., & Lloyd, S. (2018). Quantum Hopfield neural network.

    Book  Google Scholar 

  • Physical Review A. Schuld, M., & Petruccione, F. (2018). Supervised Learning with Quantum Computers. Springer.

    Google Scholar 

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Authors and Affiliations

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Correspondence to Niels Neumann, Frank Phillipson or Richard Versluis.

Additional information

Niels Neumann MSc Niels Neumann MSc is a scientist at TNO. He works on (near term) applications of quantum computers and quantum networks. He studied mathematics and physics.

Dr. Frank Phillipson Dr. Frank Phillipson is senior scientist at TNO. He leads the project team within TNO that studies applications and algorithms for near future use on quantum computers and quantum simulators. He studied econometrics and mathematics and has a PhD in applied mathematics.

Ir. Richard Versluis Ir. Richard Versluis is principal systems engineer and lead scientist quantum technology at TNO. He is the system architect of Quantum Inspire, an online open access quantum computing platform.

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Neumann, N., Phillipson, F. & Versluis, R. Machine learning in the quantum era. Digitale Welt 3, 24–29 (2019). https://doi.org/10.1007/s42354-019-0164-0

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  • DOI: https://doi.org/10.1007/s42354-019-0164-0

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