State Space Estimation
State Space Estimation is a statistical inference method that belongs to the class of dynamic system modeling techniques, distinguished by its use of latent state variables and observed measurements to recursively estimate the evolving internal state of a system over time according to probabilistic state-space models.
1.3K
Publications
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2.8K
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1K
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Publications per year
2017–2026
280
Parents
1.3K
On Gibbs sampling for state space models
Chris Carter, Robert Kohn · Biometrika · 1994 · 2K citations
Introduction to Multiple Time Series Analysis
Ian T. Jolliffe, Helmut Lütkepohl, Helmut Lütkepohl · Technometrics · 1993 · 2K citations
Business, Economics, Econometrics +16
Monte Carlo localization for mobile robots
Frank Dellaert, D. Fox, Wolfram Burgard et al. · 2003 · 1.6K citations · Full text
Monte Carlo localization: efficient position estimation for mobile robots
Dieter Fox, Wolfram Burgard, Frank Dellaert et al. · 1999 · 1.1K citations
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Massachusetts Institute of Technology
Cambridge, United States
18 h-index
43 publications
6.9K citations
Jiangnan University
Wuxi, China
17 h-index
48 publications
4K citations

Linköping University
Linköping, Sweden
17 h-index
38 publications
1.9K citations

Delft University of Technology
Delft, The Netherlands
16 h-index
42 publications
3K citations
University of Michigan
Ann Arbor, United States
15 h-index
27 publications
2.1K citations
Tsinghua University
Beijing, China
15 h-index
40 publications
1.2K citations
University of California, Berkeley
Berkeley, United States
15 h-index
27 publications
1.9K citations
KU Leuven
Leuven, Belgium
14 h-index
37 publications
4.1K citations
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44 publications · 3.8K citations
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55 publications · 4.9K citations
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Repository · 24 publications · 811 citations
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