Deterministic Inverse Problems
Deterministic Inverse Problems is an inverse problem framework in which the underlying system is modeled without probabilistic assumptions, relying solely on exact mathematical relationships to uniquely infer unknown parameters from observed data.
67
Publications
3.7K
Citations
186
Authors
117
Institutions
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2017–2026
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Parents
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Sparse deterministic approximation of Bayesian inverse problems
C. Schwab, Andrew M. Stuart · Inverse Problems · 2012 · 111 citations · Full text
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NOAA Center for Satellite Applications and Research, United States
2 publications · 48 citations
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Montreal Neurological Institute and Hospital, Canada
2 publications · 69 citations
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Centre National de la Recherche Scientifique
Paris, France
3 h-index
5 publications
155 citations
The University of Texas at Austin
Austin, United States
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3 publications
127 citations
Rensselaer Polytechnic Institute
Troy, United States
2 h-index
4 publications
155 citations
University of Maryland, College Park
College Park, United States
2 h-index
4 publications
96 citations

Johannes Kepler University of Linz
Linz, Austria
2 h-index
3 publications
131 citations
Rutgers, The State University of New Jersey
New Brunswick, United States
2 h-index
3 publications
305 citations
North Carolina State University
Raleigh, United States
2 h-index
3 publications
215 citations

Delft University of Technology
Delft, The Netherlands
2 h-index
4 publications
246 citations
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10 publications · 462 citations
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4 publications · 192 citations
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2 publications · 69 citations
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2 publications · 59 citations
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2 publications · 48 citations
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