Quantum Circuit Learning

Quantum Circuit Learning is a computational framework within quantum machine learning that integrates parameterized quantum circuits with classical optimization techniques to enable the training of quantum models for data-driven tasks.

273

Publications

22K

Citations

820

Authors

410

Institutions

Publications per year

2017–2026

237

Authors

820

  1. AP
    Alejandro Perdomo‐Ortiz

    Ames Research Center, United States

    10 publications · 867 citations

    10

    h-index

  2. DT
    Dacheng Tao

    The University of Sydney, Australia

    7 publications · 363 citations

    7

    h-index

  3. HH
    Hsin-Yuan Huang

    California Institute of Technology, United States

    5 publications · 272 citations

    5

    h-index

  4. TL
    Tongliang Liu

    The University of Sydney, Australia

    5 publications · 316 citations

    5

    h-index

  5. MH
    Min-Hsiu Hsieh

    University of Technology Sydney, Australia

    5 publications · 261 citations

    5

    h-index

1–5 of 820

Venues

  1. arXiv (Cornell University)

    Repository · 31 publications · 871 citations

    15

    h-index

  2. Physical review. A/Physical review, A

    PRA · 19 publications · 4.1K citations

    15

    h-index

  3. PRX Quantum

    9 publications · 995 citations

    9

    h-index

  4. Physical Review Letters

    PRL · 8 publications · 817 citations

    8

    h-index

  5. Quantum Machine Intelligence

    8 publications · 640 citations

    8

    h-index

1–5