Inverse problem for Yang-Mills-Higgs fields

Lauri Oksanen, Xi Chen, Matti Lassas, Gabriel Paternain

The Lorentzian scattering rigidity problem and rigidity of stationary metrics

Plamen Stefanov

Resonant forms at zero for dissipative Anosov flows

Mihajlo Cekic, Gabriel Paternain

Ray transform problems arising from seismology

Joonas Ilmavirta

X-ray mapping properties and degenerately elliptic operators

Yuzhou Zou, Francois Monard, Rohit Kumar Mishra

The range of the non-Abelian X-ray transform

Jan Bohr

Marked length spectrum rigidity for Anosov surfaces

Thibault Lefeuvre

Weakly nonlinear geometric optics for the Westervelt equation

Nikolas Eptaminitakis

The Calderón problem for space-time fractional parabolic operators with variable coefficients

Agnid Banerjee, Soumen Senapati

Rich tomography reconstruction problems in applications.

William Lionheart

Localized artifacts in medical imaging

Rima Alaifari

Explicit inversion of momentum ray transform

Shubham Ramkisan Jathar

Equivariant Neural Networks for Indirect Measurements

Nick Heilenkötter, Matthias Beckmann

Bayesian MRI reconstruction with joint uncertainty estimation using diffusion priors

Guanxiong Luo, Moritz Blumenthal, Martin Heide, Martin Uecker

Utilizing variational autoencoders in the Bayesian inverse problem of photoacoustic tomography

Teemu Sahlström, Tanja Tarvainen

Scalable Bayesian uncertainty quantification with learned convex regularisers

Tobías Ignacio Liaudat, Marta Betcke, Jason D. McEwen, Marcelo Pereyra

Calibration-Based Probabilistic Error Bounds for Inverse Problems in Imaging

Martin Zach, Andreas Habring, Martin Holler, Dominik Narnhofer, Thomas Pock

Posterior-Variance-Based Error Quantification for Inverse Problems in Imaging

Dominik Narnhofer, Andreas Habring, Martin Holler, Thomas Pock

How to sample from a posterior like you sample from a prior

Babak Maboudi Afkham, Matthias Chung, Julianne Chung

Uncertainty Quantification for Computed Tomography via the Linearised Deep Image Prior

Riccardo Barbano

Accelerating MCMC for imaging science by using an implicit Langevin algorithm

Teresa Klatzer, Konstantinos Zygalakis, Paul Dobson, Marcelo Pereyra, Yoann Altmann

Quasi-Monte Carlo methods for Bayesian optimal experimental design problems governed by PDEs

Vesa Kaarnioja

Maximum marginal likelihood estimation of regularisation parameters in Plug & Play Bayesian estimation: Application to non-blind and semi-blind image deconvolution

Charlesquin Kemajou Mbakam, Marcelo Pereyra, Jean-Francois Giovannelli

Choosing observations to mitigate model error in Bayesian inverse problems

Nada Cvetkovic, Han Cheng Lie, Harshit Bansal, Karen Veroy--Grepl

Deep learning MR image reconstruction and task-based evaluation

Florian Knoll, Jinho Kim, Marc Vornehm, Vanya Saksena, Zhengguo Tan, Bernhard Kainz

Learning Fourier sampling schemes for MRI by density optimization

Alban Gossard, Frédéric de Gournay, Pierre Weiss

Acceleration strategies for Magnetic Resonance Spin Tomography in Time-Domain (MR‐STAT) reconstructions

Hongyan Liu, Oscar van der Heide, Mandija Stefano, Versteeg Edwin, Fuderer Miha, Cornelis A.T. van den Berg, Alessandro Sbrizzi

Learning Spatio-Temporal Regularization Parameter-Maps for Total Variation-Minimization Reconstruction in Dynamic Cardiac MRI

Andreas Kofler, Fabian Altekrüger, Fatima Antarou Ba, Christoph Kolbitsch, Evangelos Papoutsellis, David Schote, Clemens Sirotenko, Felix Frederik Zimmermann, Kostas Papafitsoros

MRI Pulse Design via discrete-valued optimal control

Christian Clason

Null Space Networks for undersampled Fourier data

Markus Haltmeier

Deep Learning Approaches for Non-Linear Inverse Problems in MRI Reconstruction

Moritz Blumenthal, Guanxiong Luo, Martin Schilling, Martin Uecker

Mathematical Methods in Parallel MRI

Benjamin Kocurov