Quantum Transfer Learning

Quantum Transfer Learning is a machine learning framework that leverages pre-trained quantum models on source tasks to enhance the learning performance of target tasks by transferring quantum-encoded knowledge across related domains or datasets.

57

Publications

3K

Citations

193

Authors

114

Institutions

Publications per year

2017–2026

51

Authors

193

  1. EA
    Erdi Acar

    Çanakkale Onsekiz Mart Üniversitesi, Türkiye

    2 publications · 58 citations

    2

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  2. İY
    İhsan Yılmaz

    Çanakkale Onsekiz Mart Üniversitesi, Türkiye

    2 publications · 58 citations

    2

    h-index

  3. JT
    Javier Tejedor

    Universidad Autónoma de Madrid, Spain

    2 publications · 60 citations

    2

    h-index

  4. MS
    Muhammad Sharif

    COMSATS University Islamabad, Pakistan

    2 publications · 509 citations

    2

    h-index

  5. TS
    Tayyaba Shahwar

    Government College University, Lahore, Pakistan

    2 publications · 127 citations

    2

    h-index

1–5 of 193

Venues

  1. Neurocomputing

    3 publications · 220 citations

    3

    h-index

  2. arXiv (Cornell University)

    Repository · 3 publications · 50 citations

    3

    h-index

  3. 2

    h-index

  4. Expert Systems with Applications

    2 publications · 233 citations

    2

    h-index

  5. Quantum Machine Intelligence

    2 publications · 98 citations

    2

    h-index

1–5