4 papers
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…
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…