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Implementation of a Variational Quantum Circuit for Machine Learning with Compact Data Representation

  • ISAAI’19 Proceedings — Artificial Intelligence
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Authors and Affiliations

  1. http://digitaleweltmagazin.de/

    Nicholas Meinhardt, Bastiaan Dekker, Niels M. P. Neumann & Frank Phillipson

Authors
  1. Nicholas Meinhardt
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  2. Bastiaan Dekker
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  3. Niels M. P. Neumann
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  4. Frank Phillipson
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Corresponding authors

Correspondence to Nicholas Meinhardt, Bastiaan Dekker, Niels M. P. Neumann or Frank Phillipson.

Additional information

Nicholas Meinhardt Nicholas Meinhardt studies physics at ETH Zurich with focus on quantum optics and quantum information. As an intern at TNO he works on quantum algorithms for machine learning and recently started his graduation project in this field.

Bastiaan Dekker Bastiaan Dekker is a scientist at TNO working on innovative signal processing methods such as machine learning. He studied applied physics.

Niels Neumann Niels Neumann is a scientist at TNO. He works on applications of quantum computers and -networks. He studied mathematics and physics.

Frank Phillipson 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.

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Meinhardt, N., Dekker, B., Neumann, N.M.P. et al. Implementation of a Variational Quantum Circuit for Machine Learning with Compact Data Representation. Digitale Welt 4, 95–101 (2020). https://doi.org/10.1007/s42354-019-0242-3

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