Programme

Monday 4th (Tutorial Day)

Time Speaker Title
09:00 Joana Frontera-Pons & Grigorios Tsagkatakis Deep Learning (Part 1)
10:30 Coffee
11:00 Joana Frontera-Pons & Grigorios Tsagkatakis Deep Learning (Part 2)
12:00 Lunch
14:00 Adrienne Leonard How to go from concept to industry-ready product
15:00 Kostas Themelis Approximate Bayesian Computation (Part 1)
15:30 Coffee
16:00 Kostas Themelis Approximate Bayesian Computation (Part 2)
17:30 End of Day 1


Tuesday 5th

Time Speaker Title
09:20 Jean-Luc Starck Welcome
09:30 Domenico Marinucci Multiple testing of local maxima for detection of peaks on the (celestial) sphere
10:20 Coffee
10:50 Melis Irfan Model-based component separation exploiting sparsity
11:20 Joana Frontera-Pons Dictionary learning for photo-z estimation
11:50 Lunch
14:00 Valeryia Naumova A machine learning approach to optimal regularization: affine manifolds
14:50 Niall Jeffrey Peak Cosmology with Realistic Simulations
15:20 Coffee
15:50 Christophe Kervazo Sparse BSS in the large-scale regime
16:20 Matthieu Heitz Wasserstein Dictionary Learning
16:50 End of Day 2
19:30 Cocktails and Social Dinner


Wednesday 6th

Time Speaker Title
09:30 Emmanuel Soubies Dictionary Learning Based on Sparse Distribution Tomography for 3D Deconvolution Microscopy
10:20 Coffee
10:50 Philippe Ciuciu Combined sparse k-space sampling and parallel imaging for high resolution MRI at 7 Tesla
11:20 Loubna El Gueddari Combination of parallel imaging and compressed sensing for high acceleration factor at 7T
11:50 Lunch
14:00 Carola-Bibiane Schönlieb Learning variational models in imaging by bilevel and quotient optimisation
14:50 George Tzagkarakis Nonlinear Manifold Learning for Financial Markets Integration
15:20 Coffee
15:50 End of Day 3