Sample-efficient Robot Learning
Sample-Efficient Robot Learning is a model-based robot learning paradigm that belongs to the class of data-driven robotic control methods, distinguished by its focus on minimizing the number of interaction samples required to achieve competent task performance through informed use of models, priors, or structured exploration.
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3.2K
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249
Authors
71
Institutions
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2017–2026
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University of California, Berkeley
Berkeley, United States
8 h-index
22 publications
1.3K citations
Google (United States)
Mountain View, United States
4 h-index
20 publications
1.1K citations
Carnegie Mellon University
Pittsburgh, United States
3 h-index
3 publications
146 citations
Aalto University
Espoo, Finland
3 h-index
7 publications
103 citations

Nara Institute of Science and Technology
Ikoma, Japan
3 h-index
8 publications
683 citations
University of Washington
Seattle, United States
2 h-index
3 publications
503 citations
The University of Texas at Austin
Austin, United States
2 h-index
4 publications
301 citations
ETH Zurich
Zurich, Switzerland
2 h-index
10 publications
1.5K citations
1–8 of 71
Repository · 29 publications · 1.2K citations
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10 publications · 496 citations
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IJRR · 2 publications · 84 citations
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Conference · 2 publications · 49 citations
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1 publications · 179 citations
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