Ensemble Uncertainty Estimation

Ensemble Uncertainty Estimation is a method in uncertainty quantification that estimates predictive uncertainty by aggregating the outputs of multiple models trained independently, thereby capturing model variance through the diversity of ensemble members.

139

Publications

9.3K

Citations

499

Authors

269

Institutions

Publications per year

2017–2026

84

Authors

499

  1. AM
    Andrey Malinin

    University of Cambridge, United Kingdom

    6 publications · 237 citations

    6

    h-index

  2. YG
    Yarin Gal

    University of Oxford, United Kingdom

    6 publications · 562 citations

    6

    h-index

  3. MG
    Mark Gales

    University of Cambridge, United Kingdom

    5 publications · 203 citations

    5

    h-index

  4. JV
    Joost van Amersfoort

    University of Oxford, United Kingdom

    4 publications · 337 citations

    4

    h-index

  5. MH
    Markus Holopainen

    University of Helsinki, Finland

    4 publications · 166 citations

    4

    h-index

1–5 of 499

Venues

  1. arXiv (Cornell University)

    Repository · 20 publications · 1.2K citations

    17

    h-index

  2. 4

    h-index

  3. Weather and Forecasting

    3 publications · 89 citations

    3

    h-index

  4. Earth System Dynamics

    3 publications · 318 citations

    3

    h-index

  5. SSRN Electronic Journal

    Repository · 3 publications · 85 citations

    3

    h-index

1–5