Bayesian Uncertainty Visualization
Bayesian Uncertainty Visualization is a visualization method that specifically represents epistemic and aleatoric uncertainties derived from Bayesian probabilistic models by encoding posterior distributions, credible intervals, or predictive uncertainties into visual constructs to support interpretation and decision-making under uncertainty.
16
Publications
610
Citations
43
Authors
21
Institutions
Publications per year
2017–2026
11
16
Displaying Uncertainty With Shading
Christopher Jackson · The American Statistician · 2008 · 85 citations
Computing, Biostatistics, Statistics +12
Dries Landuyt, Katrien Van der Biest, Steven Broekx et al. · Environmental Modelling & Software · 2015 · 57 citations
1–5 of 16
43
4
h-index
4
h-index
2
h-index
2
h-index
1
h-index
1–5 of 43
21
University of Kassel
Kassel, Germany
4 h-index
4 publications
119 citations

University of Freiburg
Freiburg im Breisgau, Germany
2 h-index
2 publications
66 citations
University of Education Freiburg
Freiburg, Germany
2 h-index
2 publications
53 citations
Heidelberg University of Education
Heidelberg, Germany
2 h-index
2 publications
37 citations

Tokyo University of Agriculture and Technology
Tokyo, Japan
1 h-index
4 publications
72 citations
University of Oregon
Eugene, United States
1 h-index
1 publications
30 citations

Pacific Northwest National Laboratory
Richland, United States
1 h-index
4 publications
120 citations
Southwest University of Science and Technology
Mianyang, China
1 h-index
5 publications
95 citations
1–8 of 21
TVCG · 3 publications · 176 citations
3
h-index
3 publications · 107 citations
3
h-index
1 publications · 19 citations
1
h-index
1 publications · 11 citations
1
h-index
1 publications · 85 citations
1
h-index
1–5