M4. New Trends in Regularization Theory

Due to the ill-posedness of most linear and nonlinear inverse problems one needs regularization techniques for their stable approximate solution. The regularization theory is well developed for problems in Hilbert spaces, and during the last years many results have also been achieved for problems in Banach spaces. However, there are still many challenging questions, and permanently new classes of inverse problems occur, motivated by applications from natural sciences, engineering and finance.

We want to bring together experts and young researchers working in this field to discuss new results in the analysis and numerics of inverse and ill-posed problems.

Organizers:
Stefan Kindermann, Johannes Kepler University Linz, Austria, This email address is being protected from spambots. You need JavaScript enabled to view it.
Robert Plato, University Siegen, Germany, This email address is being protected from spambots. You need JavaScript enabled to view it.
Bernd Hofmann, Technische Universität Chemnitz, Germany, This email address is being protected from spambots. You need JavaScript enabled to view it.

Invited Speakers:
Harshit Bajpai, Indian Institute of Technology Roorkee, India, This email address is being protected from spambots. You need JavaScript enabled to view it.
Data-assisted iterative regularization via graph Laplacians: theory and applications

Christina Brandt, Universität Greifswald, Germany, This email address is being protected from spambots. You need JavaScript enabled to view it. 
Regularization methods for time-dependent magnetic particle imaging

Kristian Bredies, Universität Graz, Austria, This email address is being protected from spambots. You need JavaScript enabled to view it. 
Infinite infimal convolution regularization: concepts, models and optimization

Bastian Dittrich, Universität Würzburg, Germany, This email address is being protected from spambots. You need JavaScript enabled to view it. 
Tikhonov regularization with $\ell^0$-constraint

Sarah Eberle-Blick, Katholische Universität Eichstätt-Ingolstadt, Germany, This email address is being protected from spambots. You need JavaScript enabled to view it. 
A monotonicity-based regularization approach to shape reconstruction for the Helmholtz equation

Andrea Ebner, Universität Innsbruck, Austria, This email address is being protected from spambots. You need JavaScript enabled to view it. 
Learning tight frame decompositions via manifold optimization for inverse problem regularization

Thorsten Hohage, Universität Göttingen, Germany, This email address is being protected from spambots. You need JavaScript enabled to view it.
Inverse problems in quantum statistics and their regularization

Simon Hubmer, Johannes Kepler Universität Linz, Austria, This email address is being protected from spambots. You need JavaScript enabled to view it. 
The SCD Semismooth* Newton method for the efficient minimization of Tikhonov functionals

Tim Jahn, Technische Universität Berlin, Germany, This email address is being protected from spambots. You need JavaScript enabled to view it.
Dimensionality reduction of statistical inverse problems through pretraining

Barbara Kaltenbacher, Universität Klagenfurt, Austria, This email address is being protected from spambots. You need JavaScript enabled to view it. 
All-at-once Kaczmarz methods for time dependent problems

Tram Thi Ngoc Nguyen, MPI Solar Systems Research, Göttingen, Germany, This email address is being protected from spambots. You need JavaScript enabled to view it. 
The extended adjoint state and nonlinearity in correlation-based passive imaging

Ronny Ramlau, Johannes Kepler Universität Linz, Austria, This email address is being protected from spambots. You need JavaScript enabled to view it. 
On the use of Arnoldi-type decompositions for the regularization of inverse problems

Elena Resmerita, Universität Klagenfurt, Austria, This email address is being protected from spambots. You need JavaScript enabled to view it.  
A unified variational framework for deblurring images under multiplicative noise

Otmar Scherzer, Universität Wien, Austria, This email address is being protected from spambots. You need JavaScript enabled to view it. 
Regularization methods for nonlinear inverse problems

Tobias Wolf, Université Caen Normandie, France, This email address is being protected from spambots. You need JavaScript enabled to view it.
Gradient flow training dynamics for infinite-dimensional inverse problems from finite measurements