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
Parents
139
Locally Weighted Ensemble Clustering
Dong Huang, Chang‐Dong Wang, Jianhuang Lai · IEEE Transactions on Cybernetics · 2017 · 374 citations · Full text
Computing, Data Science, Data Mining +12
Emil M. Constantinescu, Víctor M. Zavala, Matthew Rocklin et al. · IEEE Transactions on Power Systems · 2010 · 259 citations
Natural Sciences, Computational Engineering, Meteorology +17
1–5 of 139
499
6
h-index
6
h-index
5
h-index
4
h-index
4
h-index
1–5 of 499
269

Centre National de la Recherche Scientifique
Paris, France
9 h-index
17 publications
1.1K citations
University of Cambridge
Cambridge, United Kingdom
8 h-index
14 publications
510 citations
University of Oxford
Oxford, United Kingdom
7 h-index
21 publications
1K citations

NSF National Center for Atmospheric Research
Boulder, United States
6 h-index
7 publications
711 citations
University of Washington
Seattle, United States
5 h-index
11 publications
463 citations
Goddard Space Flight Center
Greenbelt, United States
5 h-index
17 publications
955 citations
Yandex (Russia)
Moscow, Russia
4 h-index
4 publications
121 citations
Columbia University
New York, United States
3 h-index
4 publications
179 citations
1–8 of 269
Repository · 20 publications · 1.2K citations
17
h-index
4 publications · 1.4K citations
4
h-index
3 publications · 89 citations
3
h-index
3 publications · 318 citations
3
h-index
Repository · 3 publications · 85 citations
3
h-index
1–5