Variation Of Information

Variation of Information is a metric in information theory that quantifies the distance between two clusterings by measuring the sum of the conditional entropies of each clustering given the other, thereby capturing the amount of information lost or gained when transitioning from one clustering to another.

27

Publications

2.7K

Citations

53

Authors

26

Institutions

Publications per year

2017–2026

8

Authors

53

  1. VS
    Vladimir S. Lerner

    Marina Del Rey Hospital, United States

    2 publications · 32 citations

    2

    h-index

  2. SK
    S. Kullback

    George Washington University, United States

    2 publications · 397 citations

    2

    h-index

  3. FY
    Fan Yang

    Tencent (China), China

    1 publications · 154 citations

    1

    h-index

  4. ZH
    Zongbo Han

    Tianjin University, China

    1 publications · 154 citations

    1

    h-index

  5. YJ
    Yihao Jiang

    Zhejiang Gongshang University, China

    1 publications · 23 citations

    1

    h-index

1–5 of 53

Venues

  1. IEEE Transactions on Information Theory

    3 publications · 445 citations

    3

    h-index

  2. Problems of Information Transmission

    2 publications · 29 citations

    2

    h-index

  3. Review of Financial Studies

    1 publications · 74 citations

    1

    h-index

  4. Journal of Statistical Mechanics Theory and Experiment

    JSTAT · 1 publications · 44 citations

    1

    h-index

  5. Informatica

    1 publications · 154 citations

    1

    h-index

1–5