Bayesian Uncertainty

Bayesian Uncertainty is a formal framework for representing and updating epistemic uncertainty through probabilistic inference, distinguished by its reliance on Bayes' theorem to quantify belief distributions over hypotheses given observed evidence.

378

Publications

26.5K

Citations

1K

Authors

474

Institutions

Publications per year

2017–2026

135

Authors

1K

  1. CP
    Costas Papadimitriou

    University of Thessaly, Greece

    9 publications · 525 citations

    9

    h-index

  2. PK
    Petros Koumoutsakos

    ETH Zurich, Switzerland

    6 publications · 451 citations

    6

    h-index

  3. CE
    Clemens Elster

    Physikalisch-Technische Bundesanstalt, Germany

    6 publications · 181 citations

    6

    h-index

  4. PA
    Panagiotis Angelikopoulos

    ETH Zurich, Switzerland

    5 publications · 433 citations

    5

    h-index

  5. MB
    Michael Beer

    University of Liverpool, United Kingdom

    4 publications · 145 citations

    4

    h-index

1–5 of 1K

Venues

  1. arXiv (Cornell University)

    Repository · 15 publications · 1.1K citations

    12

    h-index

  2. Metrologia

    12 publications · 547 citations

    12

    h-index

  3. Reliability Engineering & System Safety

    9 publications · 694 citations

    9

    h-index

  4. Water Resources Research

    8 publications · 1.8K citations

    8

    h-index

  5. Mechanical Systems and Signal Processing

    MSSP · 7 publications · 228 citations

    7

    h-index

1–5