Program
Wednesday 4 September 2024
Welcome and Registration 10:00 - 11:00
11:00 - 11:10
Opening
Marco Prato, Università di Modena e Reggio Emilia
11:10 - 11:50
Off-the-grid regularisation promoting curves for inverse problems in imaging
Laure Blanc-Féraud, CNRS, Université Côte d’Azur, Inria Sophia Antipolis-Mediterranée
11:50 - 12:30
Differentiating nonsmooth solutions to parametric monotone inclusion problems
Antonio Silveti-Falls, CentraleSupélec, Paris
Lunch break 12:30 - 2:00
2:00 - 2:40
Learning of optimization algorithms with convergence rates
Peter Ochs, University of Tübingen
2:40 - 3:20
A modular deep learning-based approach for Diffuse Optical Tomography reconstruction
Alessandro Benfenati, Università di Milano
Coffee break 3:20 - 3:50
3:50 - 4:30
TBA
Paola Causin, Università di Milano
4:30 - 5:10
Space-variant regularization boosted by learning techniques for tomographic imaging
Elena Morotti, Università di Bologna
Thursday 5 September 2024
9:20 - 10:00
Exact continuous Bregman relaxations of $\ell_0$-regularised criteria with non-quadratic data terms
Luca Calatroni, CNRS, Université Côte d’Azur, Inria Sophia Antipolis-Mediterranée
10:00 - 10:40
Fast first-order methods for dynamic and PDE-constrained inverse problems, as well as bilevel learning
Tuomo Valkonen, Escuela Politécnica Nacional, Quito
Coffee break 10:40 - 11:10
11:10 - 11:50
Diffusion-based models meet image priors
Erich Kobler, University Hospital Bonn
11:50 - 12:30
Poster session
Lunch break 12:30 - 2:00
Afternoon session dedicated to the memory of Mario Bertero
2:00 - 2:10
Session opening
Alessandro Verri, Università di Genova
2:10 - 2:50
On the square-root LASSO
Christine De Mol, Université libre de Bruxelles
2:50 - 3:30
Image scanning microscopy with single-photon array detectors: A new technology for an old inverse problem
Giuseppe Vicidomini, Istituto Italiano di Tecnologia
Coffee break 3:30 - 4:00
4:00 - 4:40
Implicit regularization by overparametrization
Silvia Villa, Università di Genova
4:40 - 5:20
Risk estimation for Poisson inverse problems
Federico Benvenuto, Università di Genova
Social event & dinner 6:30 - 11:30
Friday 6 September 2024
9:20 - 10:00
Stochastic optimisation for large-scale inverse problems
Matthias Ehrhardt, University of Bath
10:00 - 10:40
Line search based stochastic gradient methods for learning applications
Federica Porta, Università di Modena e Reggio Emilia
Coffee break 10:40 - 11:10
11:10 - 11:50
Spectral stochastic gradient method with additional sampling for finite and infinite sums
Natasa Krklec Jerinkic, University of Novi Sad
11:50 - 12:30
Randomized Gauss-Newton methods for large scale nonlinear least squares
Greta Malaspina, Università di Firenze
Lunch break 12:30 - 2:00
2:00 - 2:40
Preconditioning strategies for a nested primal-dual method
Marco Donatelli, Università dell'Insubria
2:40 - 3:20
Regularisation with optimal space-time priors
Tatiana A. Bubba, University of Bath
Closing 3:20 - 3:30