Proper Scoring Rules
Proper Scoring Rules is a scoring function used to evaluate probabilistic forecasts that elicits honest and calibrated predictions by ensuring the expected score is minimized only when the predicted probability distribution matches the true distribution.
185
Publications
21.5K
Citations
344
Authors
208
Institutions
Publications per year
2017–2026
49
185
1–5 of 185
344
8
h-index
7
h-index
6
h-index
4
h-index
4
h-index
1–5 of 344
208
Duke University
Durham, United States
11 h-index
13 publications
525 citations
Karlsruhe Institute of Technology
Karlsruhe, Germany
6 h-index
10 publications
559 citations
University of Michigan
Ann Arbor, United States
5 h-index
7 publications
1.2K citations

Harvard University Press
Cambridge, United States
5 h-index
9 publications
148 citations
University of California, Berkeley
Berkeley, United States
5 h-index
6 publications
194 citations

The University of Sydney
Sydney, Australia
4 h-index
7 publications
153 citations
Microsoft Research (United Kingdom)
Cambridge, United Kingdom
4 h-index
5 publications
75 citations
University of Washington
Seattle, United States
4 h-index
5 publications
5K citations
1–8 of 208
Repository · 11 publications · 213 citations
10
h-index
8 publications · 475 citations
8
h-index
6 publications · 343 citations
6
h-index
5 publications · 1.1K citations
5
h-index
Repository · 4 publications · 63 citations
4
h-index
1–5