What is he best known for?
The fields of study he is best known for:
- Mathematical analysis
- Artificial intelligence
- Geometry
Otmar Scherzer mainly focuses on Inverse problem, Mathematical analysis, Regularization, Nonlinear system and Mathematical optimization.
The Inverse problem study combines topics in areas such as Artificial intelligence, Applied mathematics and Computer vision.
His studies deal with areas such as Modes of convergence and Inverse as well as Mathematical analysis.
Particularly relevant to Backus–Gilbert method is his body of work in Regularization.
His Nonlinear system study combines topics from a wide range of disciplines, such as Iterative method and Well-posed problem.
His Landweber iteration study in the realm of Iterative method interacts with subjects such as A priori and a posteriori.
His most cited work include:
- A convergence analysis of the Landweber iteration for nonlinear ill-posed problems (470 citations)
- Iterative Regularization Methods for Nonlinear Ill-Posed Problems (451 citations)
- A convergence rates result for Tikhonov regularization in Banach spaces with non-smooth operators (319 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Mathematical analysis, Applied mathematics, Inverse problem, Regularization and Nonlinear system.
His work on Numerical analysis as part of his general Mathematical analysis study is frequently connected to Bingham plastic, thereby bridging the divide between different branches of science.
His studies in Applied mathematics integrate themes in fields like Landweber iteration, Variational regularization, Banach space, Hilbert space and Multiple integral.
As part of the same scientific family, Otmar Scherzer usually focuses on Inverse problem, concentrating on Radon transform and intersecting with Optics.
His biological study spans a wide range of topics, including Rate of convergence, Mathematical optimization and Well-posed problem.
His work in Mathematical optimization covers topics such as Algorithm which are related to areas like Iterative reconstruction.
He most often published in these fields:
- Mathematical analysis (39.18%)
- Applied mathematics (31.51%)
- Inverse problem (29.04%)
What were the highlights of his more recent work (between 2015-2021)?
- Applied mathematics (31.51%)
- Inverse problem (29.04%)
- Regularization (23.29%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Applied mathematics, Inverse problem, Regularization, Mathematical analysis and Nonlinear system.
His primary area of study in Applied mathematics is in the field of Well-posed problem.
His work deals with themes such as Helmholtz equation, Optical coherence tomography, Data-driven, Radon transform and Photoacoustic tomography, which intersect with Inverse problem.
Otmar Scherzer has researched Regularization in several fields, including Level set and Optimal control.
His Numerical analysis study in the realm of Mathematical analysis connects with subjects such as Bingham plastic.
The study incorporates disciplines such as Discretization and Tomography in addition to Nonlinear system.
Between 2015 and 2021, his most popular works were:
- A direct method for photoacoustic tomography with inhomogeneous sound speed (50 citations)
- Inverse Boundary Value Problem For The Helmholtz Equation: Quantitative Conditional Lipschitz Stability Estimates (16 citations)
- On the X -ray transform of planar symmetric 2-tensors (16 citations)
In his most recent research, the most cited papers focused on:
- Mathematical analysis
- Artificial intelligence
- Geometry
His primary areas of study are Applied mathematics, Inverse problem, Mathematical analysis, Regularization and Nonlinear system.
The concepts of his Applied mathematics study are interwoven with issues in Medical imaging, Hilbert space and Regular polygon.
His Inverse problem research includes themes of Helmholtz equation, Boundary value problem, Inverse, Linear combination and Wave equation.
Otmar Scherzer combines subjects such as Finite element method, Galerkin method, Attenuation and Optical coherence tomography with his study of Mathematical analysis.
His research integrates issues of Robustness and Optimal control in his study of Regularization.
His work focuses on many connections between Nonlinear system and other disciplines, such as Landweber iteration, that overlap with his field of interest in Computational mathematics, Training set and Data-driven.
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