Probabilistic Dynamics Models
Probabilistic Dynamics Models is a type of dynamics model in model-based robot learning that represents system transition probabilities using probability distributions to quantify uncertainty in predictions, distinguishing it from deterministic dynamics models by explicitly accounting for epistemic and aleatoric uncertainties in state transitions.
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Publications
4.2K
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147
Authors
87
Institutions
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2017–2026
13
Variants
Probabilistic Dynamics Model
Parents
67
Seungsu Kim, Ashwini Shukla, Aude Billard · IEEE Transactions on Robotics · 2014 · 219 citations · Full text
Engineering, Mechanical Engineering, Robotics Engineering +17
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Université Libre de Bruxelles
Brussels, Belgium
11 h-index
19 publications
1.5K citations
University of Maryland, College Park
College Park, United States
4 h-index
5 publications
278 citations
Consejo de Seguridad Nuclear
Madrid, Spain
3 h-index
4 publications
90 citations

Imperial College London
London, United Kingdom
2 h-index
2 publications
39 citations
Carnegie Mellon University
Pittsburgh, United States
2 h-index
6 publications
354 citations
Gesellschaft für Anlagen und Reaktorsicherheit
Cologne, Germany
2 h-index
4 publications
162 citations

Istanbul Technical University
Istanbul, Türkiye
2 h-index
2 publications
40 citations
University of Michigan
Ann Arbor, United States
2 h-index
3 publications
59 citations
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7 publications · 386 citations
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Repository · 6 publications · 113 citations
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5 publications · 158 citations
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2 publications · 40 citations
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2 publications · 63 citations
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