Probabilistic Reasoning
Probabilistic Reasoning is a formal framework for uncertainty reasoning that employs probability theory to represent and manipulate uncertain knowledge, distinguishing itself by quantifying uncertainty through numerical probabilities and updating beliefs via Bayes’ theorem or related statistical inference methods.
2K
Publications
138.2K
Citations
3.4K
Authors
1.2K
Institutions
Publications per year
2017–2026
353
2K
Stanley: The robot that won the DARPA Grand Challenge
Sebastian Thrun, Mike Montemerlo, Hendrik Dahlkamp et al. · Journal of Field Robotics · 2006 · 2.1K citations · Full text
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3.4K
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1.2K
Stanford University
Stanford, United States
36 h-index
97 publications
46K citations

Centre National de la Recherche Scientifique
Paris, France
27 h-index
64 publications
6K citations

Université Toulouse III - Paul Sabatier
Toulouse, France
23 h-index
55 publications
6.6K citations
Institut de Recherche en Informatique de Toulouse
Toulouse, France
21 h-index
48 publications
6.1K citations
University of California, Berkeley
Berkeley, United States
21 h-index
47 publications
5.9K citations
University of Washington
Seattle, United States
19 h-index
53 publications
6.2K citations
Carnegie Mellon University
Pittsburgh, United States
18 h-index
28 publications
2K citations
Princeton University
Princeton, United States
18 h-index
30 publications
1.9K citations
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Repository · 73 publications · 2.7K citations
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30 publications · 5.4K citations
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42 publications · 2.2K citations
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24 publications · 5.8K citations
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27 publications · 3.1K citations
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