Bayesian Decision Theory

Bayesian Decision Theory is a branch of decision theory that employs Bayesian inference to determine optimal decisions under uncertainty by updating prior beliefs with observed data to minimize expected loss or maximize expected utility.

3K

Publications

221.9K

Citations

5.2K

Authors

1.8K

Institutions

Publications per year

2017–2026

610

Authors

5.2K

  1. RL
    Robert L. Winkler

    Duke University, United States

    15 publications · 2K citations

    14

    h-index

  2. KF
    Karl Friston

    University College London, United Kingdom

    13 publications · 2.4K citations

    13

    h-index

  3. JB
    Joseph B. Kadane

    Carnegie Mellon University, United States

    13 publications · 1.3K citations

    12

    h-index

  4. RR
    Ronald R. Yager

    Iona College, United States

    10 publications · 533 citations

    11

    h-index

  5. PP
    Prakash P. Shenoy

    University of Kansas, United States

    9 publications · 768 citations

    10

    h-index

1–5 of 5.2K

Venues

  1. Journal of the American Statistical Association

    53 publications · 9.2K citations

    31

    h-index

  2. arXiv (Cornell University)

    Repository · 78 publications · 5.5K citations

    31

    h-index

  3. Management Science

    38 publications · 5.5K citations

    27

    h-index

  4. Philosophy of Science

    27 publications · 2.2K citations

    24

    h-index

  5. The American Statistician

    26 publications · 2.2K citations

    21

    h-index

1–5