Error Modeling
Error Modeling is a mathematical framework that characterizes and quantifies the deviations between a robot's intended and actual kinematic or dynamic behavior by systematically representing the sources, structure, and propagation of errors within its operational environment.
639
Publications
51.4K
Citations
1.7K
Authors
593
Institutions
Publications per year
2017–2026
189
639
Differential expression analysis for sequence count data
Simon Anders, Wolfgang Huber · Genome biology · 2010 · 16.4K citations · Full text
Differential analysis of RNA-seq incorporating quantification uncertainty
Harold Pimentel, Nicolas Bray, Suzette Puente et al. · Nature Methods · 2017 · 1.7K citations · Full text
Differential expression analysis for sequence count data
Simon Anders, Wolfgang Huber · Nature Precedings · 2010 · 989 citations · Full text
1–5 of 639
1.7K
University of Wisconsin–Milwaukee, United States
10 publications · 400 citations
10
h-index
7
h-index
6
h-index
6
h-index
5
h-index
1–5 of 1.7K
593
Tsinghua University
Beijing, China
15 h-index
61 publications
2.2K citations
Tianjin University
Tianjin, China
11 h-index
46 publications
2.4K citations

Shanghai Jiao Tong University
Shanghai, China
10 h-index
21 publications
758 citations

Huazhong University of Science and Technology
Wuhan, China
10 h-index
32 publications
2.1K citations
University of Michigan
Ann Arbor, United States
10 h-index
25 publications
1.8K citations

Centre National de la Recherche Scientifique
Paris, France
10 h-index
23 publications
1.4K citations

Xi'an Jiaotong University
Xi'an, China
9 h-index
44 publications
2K citations
Carnegie Mellon University
Pittsburgh, United States
8 h-index
12 publications
1.6K citations
1–8 of 593
40 publications · 1.7K citations
27
h-index
10 publications · 791 citations
10
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IJRR · 8 publications · 1.1K citations
8
h-index
8 publications · 583 citations
8
h-index
7 publications · 299 citations
7
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1–5