Transfer Learning Across Environments

Transfer Learning Across Environments is a genomic selection methodology that leverages genetic and environmental data from multiple contexts to improve prediction accuracy in target environments by transferring knowledge from related but distinct environments through shared genomic patterns.

8

Publications

534

Citations

41

Authors

27

Institutions

Publications per year

2017–2026

6

Authors

41

  1. NW
    Nimisha Wagle

    University of California, Davis, United States

    1 publications · 12 citations

    1

    h-index

  2. ZZ
    Zhi‐Hui Zhan

    South China University of Technology, China

    1 publications · 107 citations

    1

    h-index

  3. JA
    Juliana Alves Pereira

    Pontifícia Universidade Católica do Rio de Janeiro, Brazil

    1 publications · 62 citations

    1

    h-index

  4. HB
    Henry Been‐Lirn Duh

    National University of Singapore, Singapore

    1 publications · 107 citations

    1

    h-index

  5. KZ
    Kun Zhang

    Carnegie Mellon University, United States

    1 publications · 23 citations

    1

    h-index

1–5 of 41

Venues

  1. IEEE Transactions on Software Engineering

    TSE · 1 publications · 62 citations

    1

    h-index

  2. IEEE Transactions on Wireless Communications

    1 publications · 61 citations

    1

    h-index

  3. Mechanical Systems and Signal Processing

    MSSP · 1 publications · 170 citations

    1

    h-index

  4. IEEE Transactions on Mobile Computing

    TMCCI · 1 publications · 23 citations

    1

    h-index

  5. 1

    h-index

1–5