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Monday 22 May

12.20-12.30 pm Introductory Remarks
12.30-1.10 pm  Learning data-driven priors for image reconstruction: From bilevel optimisation to neural network-based unrolled schemes
Kostas Papafitsoros
Queen Mary University of London
1.10-1.50 pm   Bayesian inference with data-driven priors encoded by neural networks
Marcelo Pereyra
Herriot-Watt University
1.50-2.30 pm   Towards efficient and robust data-driven optimization
Billy Junqi Tang
University of Birmingham
2.30-2.40 pm   Coffee & Tea Break
2.40-3.20 pm   Regularization by inexact Krylov methods
Silvia Gazzola
University of Bath
3.20-4.00 pm   Random descent for least squares functionals
Dirk Lorenz
Technische Universität Braunschweig
4.00-4.40 pm   Ensemble Kalman inversion for tomographic imaging
Marco Iglesias
University of Nottingham
4.40-5.00 pm   Coffee & Tea Break
5.00-6.00 pm   Lightning Talks
Riccardo Barbano University College London
Uncertainty quantification for computed tomography via the linearised Deep Image Prior
Michael Causon University of Nottingham
Bayesian inversion in resin transfer moulding
Charlesquin Kemajou Mbakam Herriot-Watt University
Maximum marginal likelihood estimation of the regularisation parameters in Plug & Play Bayesian estimation: Application to non-blind and semi-blind image deconvolution
Michael Tang Herriot-Watt University
A Plug-and-Play algorithm for uncertainty quantification in computational imaging
Oliver Townsend University of Bath
Undersampling Raster Scans in Spectromicroscopy for reduced dose and faster measurements

Tuesday 23 May

9.00-9.40 am   Learned stochastic primal dual method with applications in subsampled and low dose CT
Marta Betcke
University College London
9.40-10.20 am  A generalized conditional gradient method for dynamic inverse problems with optimal transport regularization
Kristian Bredies
Karl-Franzens-Universität Graz
10.20-11.00 am A primal-dual plug-and-play algorithm for computational optical imaging
Audrey Repetti
Herriot-Watt University
11.00-11.10 am Coffee & Tea Break
11.10-11.50 am Optimization algorithms and differential equations: theory and insights
Konstantinos Zygalakis
University of Edinburgh
11.50-12.30 pm Early stopping of untrained neural networks
Tim Jahn
Rheinische Friedrich-Wilhelms-Universität Bonn
12.30-1.10 pm  Structured generative models as priors for inverse problems
Neill Campbell
University of Bath