Model Identifiability
Model Identifiability is the property of a mathematical model, within the context of dynamical systems and parameter estimation, that determines whether the model's unknown parameters can be uniquely inferred from observed input-output data under ideal noise-free and error-free measurement conditions.
2.4K
Publications
169.6K
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4K
Authors
1.4K
Institutions
Publications per year
2017–2026
417
Children
Algebraic IdentifiabilityGeneric IdentifiabilityIdentifiability CriteriaIdentifiability In Stochastic ModelsIdentifiability Of Compartmental ModelsIdentifiability Of Dynamic SystemsIdentifiability Of Pharmacodynamic ModelsIdentifiability Of Pharmacokinetic ModelsIdentifiability-based Experimental DesignInput Identifiability
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Consejo Superior de Investigaciones Científicas, Spain
17 publications · 1.8K citations
16
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1.4K

Centre National de la Recherche Scientifique
Paris, France
41 h-index
245 publications
10.1K citations
Jiangnan University
Wuxi, China
32 h-index
100 publications
8K citations

Linköping University
Linköping, Sweden
31 h-index
78 publications
10.5K citations

Delft University of Technology
Delft, The Netherlands
28 h-index
117 publications
6.2K citations

University of Alberta
Edmonton, Canada
24 h-index
67 publications
4.3K citations
Columbia University
New York, United States
21 h-index
43 publications
2.4K citations
Université de Lorraine
Nancy, France
21 h-index
69 publications
2.7K citations

Uppsala University
Uppsala, Sweden
21 h-index
45 publications
3.5K citations
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208 publications · 26.9K citations
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111 publications · 7.4K citations
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40 publications · 6.5K citations
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153 publications · 4.5K citations
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40 publications · 2.5K citations
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