42 citations · 83 across the 13 of their papers we have counts for
6 papers · 1 filter
A Distributed Plug-and-Play MCMC Algorithm for High-Dimensional Inverse Problems
Maxime Bouton, Pierre-Antoine Thouvenin, Audrey Repetti +1
Markov Chain Monte Carlo (MCMC) algorithms are standard approaches to solve imaging inverse problems and quantify estimation uncertainties, a key requirement in absence of ground-t…
Tracers of the ionization fraction in dense and translucent molecular gas: II. Using mm observations to constrain ionization fraction across Orion B
Ivana Bešlić, Maryvonne Gerin, Viviana V. Guzmán +28
The ionization fraction () is a crucial parameter of interstellar gas, yet estimating it requires deep knowledge of molecular gas chemistry…
Time and covariance smoothing for restoration of bivariate signals
Yusuf Yigit Pilavci, Pierre Palud, Julien Flamant +3
In many applications and physical phenomena, bivariate signals are polarized, i.e. they trace an elliptical trajectory over time when viewed in the 2D planes of their two component…
Beetroots: spatially-regularized Bayesian inference of physical parameter maps -- Application to Orion
Pierre Palud, Emeric Bron, Pierre Chainais +28
The current generation of millimeter receivers is able to produce cubes of 800 000 pixels by 200 000 frequency channels to cover several square degrees over the 3 mm atmospheric wi…
Estimating the dense gas mass of molecular clouds using spatially unresolved 3 mm line observations
Antoine Zakardjian, Annie Hughes, Jérôme Pety +28
We aim to develop a new method to infer the sub-beam probability density function (PDF) of H2 column densities and the dense gas mass within molecular clouds using spatially unreso…
Denoising bivariate signals via smoothing and polarization priors
Yusuf Yigit Pilavci, Jérémie Boulanger, Pierre-Antoine Thouvenin +1
We propose two formulations to leverage the geometric properties of bivariate signals for dealing with the denoising problem. In doing so, we use the instantaneous Stokes parameter…