November 28-December 2, 2022

- Otmar Scherzer (RICAM & University of Vienna, Austria)
- Ronny Ramlau (RICAM & University of Linz, Austria)

The focus of this workshop lies on the numerical solution of large scale inverse problems.

Topics of this workshop are mathematical modeling, simplification and surrogate modeling,
operator learning and efficient numerical implementation and algorithmic aspects. Another
aspect of this workshop concerns the analysis of recently developed numerical methods.

We will bring together researchers working on practical problems, researchers in mathematical
modeling and algorithmic aspects of inverse problems.

- Time Schedule (PDF)

- Giovanni S. Alberti (University of Genoa):

Compressed sensing for the sparse Radon transform

Slides - Andrea Aspri (Università degli Studi di Milano):

Phase-field approaches in elastic inverse problems

Slides - Jean-Francois Aujol (Université Bordeaux):

FISTA is an automatic geometrically optimized algorithm for strongly convex functions - Elena Beretta (New York University Abu Dhabi):

On the identification of cavities in a nonlinear model arising from cardiac electrophysiology

Slides - Martin Burger (FAU Erlangen-Nürnberg):

Understanding learning approaches for inverse problems - Kristian Bredies (University of Graz):

A generalized conditional gradient method for dynamic inverse problems with optimal transport regularization

Slides - Antonin Chambolle (CEREMADE, CNRS, Université Paris-Dauphine PSL):

First order methods for Wasserstein distance and barycenter problems

Slides - Raymond Chan (City University of Hong Kong):

Selecting Regularization Parameters for Nuclear Norm Type Minimization Problems

Slides - Matthias Chung (Emory University):

The Art of Repeatedly Project your Problems

Slides - Maarten de Hoop (Rice University ):

Spectral rigidity and neural lens rigidity of terrestrial planets - Marco Donatelli (University of Insubria):

Fractional graph Laplacian for image reconstruction

Slides - Vladimir Druskin (WPI):

Reduced order modeling inversion of mono static data in a multi-scattering environment - Daniel Gerth (TU Chemnitz)
- Martin Hanke (Johannes Gutenberg University):

The inverse Henderson problem - Andreas Hauptmann (University of Oulu):

Data-driven model corrections and learned iterative reconstruction

Slides - Tapio Helin (LUT University):

Statistical inverse learning and regularization by projections

Slides - Fabian Hinterer (JKU Linz):

A projected Nesterov-Kaczmarz approach to stellar population distribution reconstruction in Extragalactic Archaeology - Bernd Hofmann (TU Chemnitz):

The treatment of deautoconvolution as inverse problem, including the multidimensional case

Slides - Tim Jahn (Universität Bonn):

Complexity reduction of ill-posed integral equations

Slides - Barbara Kaltenbacher (University of Klagenfurt):

Convergence guarantees for Newton type methods in tomographic problems via range invariance

Slides - Antonio Leitao (UFSC):

On the problem of crack detection from electrical measurements

Slides - Shuai Lu (Fudan University):

Data assimilation from a viewpoint of regularization theory

Slides - Peter Maass (ZeTeM, University of Bremen)
- Serena Morigi (University of Bologna):

Deep-Plug-and-Play proximal Newton-type method with applications to nonlinear, ill-posed inverse problems - Stefano Pagani (Politecnico di Milano):

Physics-aware deep learning approach to inverse problems in cardiac electrophysiology - Sergiy Pereverzyev (RICAM):

Regularized Radon-Nikodym differentiation and some of its application

Slides - Todd Quinto (Tufts University):

Seismic imaging with generalized Radon transforms: stability of the Bolker Condition

Slides - Lothar Reichel (Kent State University)
- Elena Resmerita (University of Klagenfurt):

Multiscale iterative methods for decomposition, deblurring and denoising of images

Slides - Bill Rundell (Texas A&M University):

On Recovering imaging coefficients in a nonlinear Wave Equation

Slides - Bernadett Stadler (JKU Linz)
- Tanja Tarvainen (University of Eastern Finland):

Model reduction and modelling of uncertainties in quantitative photoacoustic tomography

Slides - Chrysoula Tsogka (University of California Merced):

Phase and absorption contrast imaging using intensity measurements

Slides - Isao Yamada (Tokyo Institute of Technology):

Fixed point strategies for nonconvexly regularized sparse estimation and hierarchical convex optimization

Slides

Johann Radon Institute for Computational and Applied Mathematics (RICAM)

Austrian Academy of Sciences

Austrian Academy of Sciences

This page was last modified on 12/02/2022 - 12:11 CEST