Quantum Machine Learning

Quantum Machine Learning is an interdisciplinary research area that integrates principles from quantum computing and machine learning, distinguished by its focus on developing algorithms and models that leverage quantum mechanical phenomena to enhance computational performance in learning tasks.

2.8K

Publications

161.8K

Citations

6K

Authors

1.8K

Institutions

Publications per year

2017–2026

2.5K

Authors

6K

  1. PJ
    Patrick J. Coles

    Los Alamos National Laboratory, United States

    33 publications · 3.2K citations

    27

    h-index

  2. MC
    M. Cerezo

    Los Alamos National Laboratory, United States

    30 publications · 2.8K citations

    25

    h-index

  3. VD
    Vedran Dunjko

    Leiden University, Netherlands

    24 publications · 2.1K citations

    19

    h-index

  4. MS
    Maria Schuld

    University of KwaZulu-Natal, South Africa

    20 publications · 7.3K citations

    19

    h-index

  5. SY
    Samuel Yen-Chi Chen

    Brookhaven National Laboratory, United States

    20 publications · 1.4K citations

    18

    h-index

1–5 of 6K

Venues

  1. Physical Review Letters

    PRL · 87 publications · 13.1K citations

    54

    h-index

  2. Physical review. A/Physical review, A

    PRA · 135 publications · 11.6K citations

    49

    h-index

  3. arXiv (Cornell University)

    Repository · 238 publications · 8.9K citations

    46

    h-index

  4. npj Quantum Information

    42 publications · 5.2K citations

    35

    h-index

  5. Quantum

    57 publications · 4.5K citations

    35

    h-index

1–5