4 papers
Getting Your Guidance Weights Right in diffusion and flow-matching posterior sampling
Liam Moroy, Jean-François Giovannelli, Yoann Altmann +3
Training-free posterior sampling methods, also known as Plug-and-Play methods, leverage pretrained unconditional diffusion or flow-matching models to solve inverse problems. Most e…
Closing the loop on-sky with a vector-Zernike wavefront sensor using a convolutional neural network as phase reconstructor
Francisco Oyarzún, Mathieu Motte, Cedric-Taissir Heritier +11
Context: The new giant segmented mirror telescopes will use adaptive optics to reach the fundamental limits in resolving power. To accomplish this, new wavefront sensors (WFS) have…
Co-design approach to aperture masking for imaging through atmospheric turbulence
Olivier Herscovici-Schiller, Laurent M. Mugnier, Alice Fontbonne +5
Aperture masking interferometry is a technique originally designed to alleviate the influence of atmospheric turbulence on images recorded on ground-based telescopes. In this commu…
Evaluating the Posterior Sampling Ability of Plug&Play Diffusion Methods in Sparse-View CT
Liam Moroy, Guillaume Bourmaud, Frédéric Champagnat +1
Plug&Play (PnP) diffusion models are state-of-the-art methods in computed tomography (CT) reconstruction. Such methods usually consider applications where the sinogram contains a s…