Canonical Correlation Analysis

Canonical Correlation Analysis is a multivariate statistical method that identifies and quantifies the linear relationships between two sets of variables by computing the maximum correlation between canonical variates formed as linear combinations of variables within each set.

3.1K

Publications

271.1K

Citations

8.7K

Authors

2.6K

Institutions

Publications per year

2017–2026

838

Authors

8.7K

  1. XG
    Xiaorong Gao

    Tsinghua University, China

    21 publications · 4.5K citations

    19

    h-index

  2. YW
    Yijun Wang

    Chinese Academy of Sciences, China

    19 publications · 2.7K citations

    18

    h-index

  3. VD
    Vince D. Calhoun

    Mind Research Network, United States

    26 publications · 1.9K citations

    18

    h-index

  4. TB
    Taha B. M. J. Ouarda

    Institut National de la Recherche Scientifique, Canada

    19 publications · 1.5K citations

    17

    h-index

  5. KL
    Karen Livescu

    Toyota Technological Institute at Chicago, United States

    16 publications · 2.8K citations

    15

    h-index

1–5 of 8.7K

Venues

  1. Journal of Climate

    37 publications · 6.5K citations

    29

    h-index

  2. arXiv (Cornell University)

    Repository · 62 publications · 3K citations

    27

    h-index

  3. Journal of Neural Engineering

    27 publications · 3.8K citations

    23

    h-index

  4. PLoS ONE

    29 publications · 2.1K citations

    22

    h-index

  5. IEEE Transactions on Signal Processing

    26 publications · 2K citations

    21

    h-index

1–5