activity
20152026
most citedRandom Matrix Improved Covariance Estimation for a Large Class of Metrics

4 citations · 10 across the 15 of their papers we have counts for

collaborators
Showing 2023Show all

5 papers · 1 filter

stat.AP2023

Online Change Detection in SAR Time-Series with Kronecker Product Structured Scaled Gaussian Models

Ammar Mian, Guillaume Ginolhac, Florent Bouchard +1

We develop the information geometry of scaled Gaussian distributions for which the covariance matrix exhibits a Kronecker product structure. This model and its geometry are then us…

math.ST2023

Intrinsic Bayesian Cramér-Rao Bound with an Application to Covariance Matrix Estimation

Florent Bouchard, Alexandre Renaux, Guillaume Ginolhac +1

This paper presents a new performance bound for estimation problems where the parameter to estimate lies in a Riemannian manifold (a smooth manifold endowed with a Riemannian metri…

stat.ML2023

The Fisher-Rao geometry of CES distributions

Florent Bouchard, Arnaud Breloy, Antoine Collas +2

When dealing with a parametric statistical model, a Riemannian manifold can naturally appear by endowing the parameter space with the Fisher information metric. The geometry induce…

stat.AP2023

Through the Wall Radar Imaging via Kronecker-structured Huber-type RPCA

Hugo Brehier, Arnaud Breloy, Chengfang Ren +1

The detection of multiple targets in an enclosed scene, from its outside, is a challenging topic of research addressed by Through-the-Wall Radar Imaging (TWRI). Traditionally, TWRI…

stat.AP2023

Robust Detection for Mills Cross Sonar

Olivier Lerda, Ammar Mian, Guillaume Ginolhac +2

Multi-array systems are widely used in sonar and radar applications. They can improve communication speeds, target discrimination, and imaging. In the case of a multibeam sonar sys…