Ill-posed Inverse Problems
Ill-Posed Inverse Problems is an inverse problem characterized by the violation of one or more of Hadamard's criteria for well-posedness—specifically, the lack of existence, uniqueness, or continuous dependence of the solution on the data—rendering its reconstruction inherently unstable and sensitive to measurement errors.
2.6K
Publications
136.6K
Citations
4.6K
Authors
1.6K
Institutions
Publications per year
2017–2026
716
Variants
Ill-posed Problems
Parents
2.6K
Blind deconvolution using a normalized sparsity measure
Dilip Krishnan, Terence Tay, Rob Fergus · 2011 · 1.1K citations
1–5 of 2.6K
4.6K
26
h-index
21
h-index
19
h-index
17
h-index
15
h-index
1–5 of 4.6K
1.6K

Centre National de la Recherche Scientifique
Paris, France
33 h-index
157 publications
6.9K citations
The University of Tokyo
Tokyo, Japan
28 h-index
57 publications
2.6K citations
University College London
London, United Kingdom
28 h-index
76 publications
4.8K citations

Johannes Kepler University of Linz
Linz, Austria
26 h-index
49 publications
4.5K citations
Chemnitz University of Technology
Chemnitz, Germany
22 h-index
50 publications
1.6K citations
Fudan University
Shanghai, China
22 h-index
53 publications
2K citations
Johann Radon Institute for Computational and Applied Mathematics
Linz, Austria
20 h-index
34 publications
1.6K citations

University of Eastern Finland
Joensuu, Finland
20 h-index
51 publications
4.4K citations
1–8 of 1.6K
279 publications · 15.3K citations
64
h-index
99 publications · 2.6K citations
29
h-index
55 publications · 1.6K citations
26
h-index
26 publications · 5.1K citations
24
h-index
Repository · 50 publications · 1.8K citations
24
h-index
1–5