28 citations · 41 across the 9 of their papers we have counts for
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Deep learning for exoplanet detection and characterization by direct imaging at high contrast
Théo Bodrito, Olivier Flasseur, Julien Mairal +3
Exoplanet imaging is a major challenge in astrophysics due to the need for high angular resolution and high contrast. We present a multi-scale statistical model for the nuisance co…
A New Statistical Model of Star Speckles for Learning to Detect and Characterize Exoplanets in Direct Imaging Observations
Théo Bodrito, Olivier Flasseur, Julien Mairal +3
The search for exoplanets is an active field in astronomy, with direct imaging as one of the most challenging methods due to faint exoplanet signals buried within stronger residual…
MODEL&CO: Exoplanet detection in angular differential imaging by learning across multiple observations
Théo Bodrito, Olivier Flasseur, Julien Mairal +3
Direct imaging of exoplanets is particularly challenging due to the high contrast between the planet and the star luminosities, and their small angular separation. In addition to t…
Combining statistical learning with deep learning for improved exoplanet detection and characterization
Olivier Flasseur, Théo Bodrito, Julien Mairal +3
In direct imaging at high contrast, the bright glare produced by the host star makes the detection and the characterization of sub-stellar companions particularly challenging. In s…
Shrinkage MMSE estimators of covariances beyond the zero-mean and stationary variance assumptions
Olivier Flasseur, Eric Thiébaut, Loïc Denis +1
We tackle covariance estimation in low-sample scenarios, employing a structured covariance matrix with shrinkage methods. These involve convexly combining a low-bias/high-variance…
Combining multi-spectral data with statistical and deep-learning models for improved exoplanet detection in direct imaging at high contrast
Olivier Flasseur, Théo Bodrito, Julien Mairal +3
Exoplanet detection by direct imaging is a difficult task: the faint signals from the objects of interest are buried under a spatially structured nuisance component induced by the…
deep PACO: Combining statistical models with deep learning for exoplanet detection and characterization in direct imaging at high contrast
Olivier Flasseur, Théo Bodrito, Julien Mairal +3
Direct imaging is an active research topic in astronomy for the detection and the characterization of young sub-stellar objects. The very high contrast between the host star and it…
REXPACO ASDI: Joint unmixing and deconvolution of the circumstellar environment by angular and spectral differential imaging
Olivier Flasseur, Loïc Denis, Éric Thiébaut +1
Angular and spectral differential imaging is an observational technique of choice to investigate the immediate vicinity of stars. The relative angular motion and spectral scaling b…
REXPACO: an algorithm for high contrast reconstruction of the circumstellar environment by angular differential imaging
Olivier Flasseur, Samuel Thé, Loïc Denis +2
Aims. The purpose of this paper is to describe a new post-processing algorithm dedicated to the reconstruction of the spatial distribution of light received from off-axis sources,…
Exoplanet Imaging Data Challenge: benchmarking the various image processing methods for exoplanet detection
F. Cantalloube, C. Gomez-Gonzalez, O. Absil +23
The Exoplanet Imaging Data Challenge is a community-wide effort meant to offer a platform for a fair and common comparison of image processing methods designed for exoplanet direct…