Deep CosmoStat Days

Session

Inverse Problems and Incertainties

16 janv. 2025, 14:30

Cassini (CEA/DAp)

16. Towards fast and scalable uncertainty quantification for scientific imaging: Application to radio interferometric imaging

Tobias Liaudat

16/01/2025 14:30

4. Deep Learning Mass Mapping with Conformal Predictions

Hubert Leterme (ENSICAEN)

16/01/2025 14:55

In this talk, I will present a plug-and-play (PnP) approach for reconstructing convergence maps from noisy shear measurements. The method aims to provide accurate estimates efficiently while eliminating the need to train a deep learning model for each new galaxy survey or region of the sky. Instead, the approach requires training a denoiser just once on simulated convergence maps corrupted...

14. Plug-and-Play PET reconstruction: a fixed point approach

16/01/2025 15:20

Deep learning has shown great promise for improving medical image reconstruction, often surpassing traditional MBIR methods. However, concerns remain about the stability and robustness of these approaches, particularly when trained on limited data. The Plug-and-Play framework offers a promising solution, showing that a stable reconstruction can be ensured, provided conditions on the plugged...

12. Joint multi-band deconvolution for Euclid and Vera C. Rubin images

Utsav Akhaury (EPFL)

16/01/2025 15:45

With the advent of surveys like Euclid and Vera C. Rubin, astrophysicists will have access to both deep, high-resolution images, and multi-band images. However, these two conditions are not simultaneously available in any single dataset. It is therefore vital to devise image deconvolution algorithms that exploit the best of the two worlds and can jointly analyse datasets spanning a range of...