Variational Quantum Generators: Generative Adversarial Quantum Machine Learning for Continuous Distributions-Reference-Cited by-同舟云学术

Variational Quantum Generators: Generative Adversarial Quantum Machine Learning for Continuous Distributions

Published:2020-12-03 Issue:1 Volume:4 Page:2000003
ISSN:2511-9044
Container-title:Advanced Quantum Technologies
language:en
Short-container-title:Adv Quantum Tech

Author:

Romero Jonathan¹,Aspuru‐Guzik Alán¹²³⁴

Affiliation:

1. Zapata Computing Inc. 100 Federal Street, 20th Floor Boston MA 02110 USA

2. Chemical Physics Theory Group Department of Chemistry and Department of Computer Science University of Toronto 80 St. George Street Toronto Ontario M5S 3H6 Canada

3. CIFAR AI Chair Vector Institute for Artificial Intelligence 661 University Ave., Suite 710 Toronto ON M5G 1M1 Canada

4. Lebovic Fellow Canadian Institute for Advanced Research (CIFAR) 661 University Ave., Suite 505 Toronto ON M5G 1M1 Canada

Funder

Army Research Office

Office of Naval Research

Publisher

Wiley

Subject

Electrical and Electronic Engineering,Computational Theory and Mathematics,Condensed Matter Physics,Mathematical Physics,Nuclear and High Energy Physics,Electronic, Optical and Magnetic Materials,Statistical and Nonlinear Physics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/qute.202000003

Reference76 articles.

1. Algorithms for quantum computation: discrete logarithms and factoring

2. Universal Quantum Simulators

3. Quantum Chemistry in the Age of Quantum Computing

4. J.Preskill arXiv:1801.00862 2018.

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