Uncertainty-aware Dynamics Learning
Uncertainty-Aware Dynamics Learning is a model-based robot learning framework that, within the class of dynamics learning methods, specifically incorporates quantified uncertainty estimates into the learning of system dynamics to improve robustness and generalization in control and planning under epistemic and aleatoric uncertainty.
16
Publications
755
Citations
50
Authors
19
Institutions
Publications per year
2017–2026
10
Parents
16
1–5 of 16
50
3
h-index
3
h-index
2
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2
h-index
Max Planck Institute for Intelligent Systems, Germany
2 publications · 39 citations
2
h-index
1–5 of 50
19
Georgia Institute of Technology
Atlanta, United States
4 h-index
13 publications
675 citations
Max Planck Society
Munich, Germany
3 h-index
8 publications
137 citations
Stanford University
Stanford, United States
2 h-index
7 publications
267 citations
Max Planck Institute for Intelligent Systems
Stuttgart, Germany
2 h-index
5 publications
92 citations
Tokyo Institute of Technology
Tokyo, Japan
1 h-index
1 publications
18 citations
Japan Science and Technology Agency
Tokyo, Japan
1 h-index
2 publications
36 citations
University of California, Berkeley
Berkeley, United States
1 h-index
3 publications
555 citations
New York University
New York, United States
1 h-index
3 publications
132 citations
1–8 of 19
Repository · 5 publications · 250 citations
5
h-index
2 publications · 93 citations
2
h-index
1 publications · 13 citations
1
h-index
1 publications · 25 citations
1
h-index
1 publications · 19 citations
1–5