Florent Bouchard

44 papers A* 2Misc 6Journal 22Unranked 13
YearRankTypeTitle / Venue / Authors
2026 J jnl
Leveraging Low-Rank Factorizations of Conditional Correlation Matrices in Graph Learning.
IEEE Trans. Signal Process.
Thu Ha Phi, Alexandre Hippert-Ferrer, Florent Bouchard, Arnaud Breloy
2026 J jnl
SPD Learn: A Geometric Deep Learning Python Library for Neural Decoding Through Trivialization.
CoRR
Bruno Aristimunha, Ce Ju, Antoine Collas, Florent Bouchard, Ammar Mian, Bertrand Thirion, Sylvain Chevallier, Reinmar J. Kobler
2025 J jnl
Beyond $R$-Barycenters: An Effective Averaging Method on Stiefel and Grassmann Manifolds.
IEEE Signal Process. Lett.
Florent Bouchard, Nils Laurent, Salem Said, Nicolas Le Bihan
2025 J jnl
Beyond R-barycenters: an effective averaging method on Stiefel and Grassmann manifolds.
CoRR
Florent Bouchard, Nils Laurent, Salem Said, Nicolas Le Bihan
2025 J jnl
Elliptical Wishart distributions: Information geometry, maximum likelihood estimator, performance analysis and statistical learning.
Signal Process.
Imen Ayadi, Florent Bouchard, Frédéric Pascal
2025 — conf
Interferometric Phase Linking with Riemannian Distances on Covariance Matrices.
EUSIPCO
Elena Grosso, Florent Bouchard, Frédéric Brigui, Guillaume Ginolhac, Arnaud Breloy
2025 J jnl
Leveraging Low-rank Factorizations of Conditional Correlation Matrices in Graph Learning.
CoRR
Thu Ha Phi, Alexandre Hippert-Ferrer, Florent Bouchard, Arnaud Breloy
2025 — conf
On the Endmembers Detection for Hyperspectral Imaging in the High-Dimensional Regime.
EUSIPCO
H. Jeannin, Florent Bouchard, Pascal Vallet, Guillaume Ginolhac, Audrey Giremus
2024 J jnl
Elliptical Wishart distributions: information geometry, maximum likelihood estimator, performance analysis and statistical learning.
CoRR
Imen Ayadi, Florent Bouchard, Frédéric Pascal
2024 J jnl
Intrinsic Bayesian Cramér-Rao Bound With an Application to Covariance Matrix Estimation.
IEEE Trans. Inf. Theory
Florent Bouchard, Alexandre Renaux, Guillaume Ginolhac, Arnaud Breloy
2024 — conf
Leveraging Standardization in Graph Learning.
EUSIPCO
Thu Ha Phi, Alexandre Hippert-Ferrer, Florent Bouchard, Arnaud Breloy
2024 J jnl
Online change detection in SAR time-series with Kronecker product structured scaled Gaussian models.
Signal Process.
Ammar Mian, Guillaume Ginolhac, Florent Bouchard, Arnaud Breloy
2024 A* conf
Random matrix theory improved Fréchet mean of symmetric positive definite matrices.
ICML
Florent Bouchard, Ammar Mian, Malik Tiomoko, Guillaume Ginolhac, Frédéric Pascal
2024 J jnl
Random matrix theory improved Fréchet mean of symmetric positive definite matrices.
CoRR
Florent Bouchard, Ammar Mian, Malik Tiomoko, Guillaume Ginolhac, Frédéric Pascal
2024 Misc conf
Robust Low-Rank Correlation Fitting.
ICASSP
Thu Ha Phi, Alexandre Hippert-Ferrer, Florent Bouchard, Arnaud Breloy
2023 Misc conf
Elliptical Wishart Distribution: Maximum Likelihood Estimator from Information Geometry.
ICASSP
Imen Ayadi, Florent Bouchard, Frédéric Pascal
2023 — conf
Learning Graphical Factor Models with Riemannian Optimization.
ECML/PKDD (4)
Alexandre Hippert-Ferrer, Florent Bouchard, Ammar Mian, Titouan Vayer, Arnaud Breloy
2023 J jnl
Natural Bayesian Cramér-Rao Bound with an Application to Covariance Estimation.
CoRR
Florent Bouchard, Alexandre Renaux, Guillaume Ginolhac, Arnaud Breloy
2023 J jnl
The Fisher-Rao geometry of CES distributions.
CoRR
Florent Bouchard, Arnaud Breloy, Antoine Collas, Alexandre Renaux, Guillaume Ginolhac
2023 — conf
t-WDA: A novel Discriminant Analysis applied to EEG classification.
EUSIPCO
Imen Ayadi, Florent Bouchard, Frédéric Pascal
2022 J jnl
Learning Graphical Factor Models with Riemannian Optimization.
CoRR
Alexandre Hippert-Ferrer, Florent Bouchard, Ammar Mian, Titouan Vayer, Arnaud Breloy
2022 Misc conf
On the Use of Geodesic Triangles between Gaussian Distributions for Classification Problems.
ICASSP
Antoine Collas, Florent Bouchard, Guillaume Ginolhac, Arnaud Breloy, Chengfang Ren, Jean Philippe Ovarlez
2022 — conf
Riemannian Classification of EEG Signals with Missing Values.
EUSIPCO
Alexandre Hippert-Ferrer, Ammar Mian, Florent Bouchard, Frédéric Pascal
2021 J jnl
A Riemannian Framework for Low-Rank Structured Elliptical Models.
IEEE Trans. Signal Process.
Florent Bouchard, Arnaud Breloy, Guillaume Ginolhac, Alexandre Renaux, Frédéric Pascal
2021 Misc conf
A Tyler-Type Estimator of Location and Scatter Leveraging Riemannian Optimization.
ICASSP
Antoine Collas, Florent Bouchard, Arnaud Breloy, Chenfang Ren, Guillaume Ginolhac, Jean Philippe Ovarlez
2021 — conf
On-line Kronecker Product Structured Covariance Estimation with Riemannian geometry for t-distributed data.
EUSIPCO
Florent Bouchard, Arnaud Breloy, Ammar Mian, Guillaume Ginolhac
2021 J jnl
Probabilistic PCA From Heteroscedastic Signals: Geometric Framework and Application to Clustering.
IEEE Trans. Signal Process.
Antoine Collas, Florent Bouchard, Arnaud Breloy, Guillaume Ginolhac, Chengfang Ren, Jean Philippe Ovarlez
2021 J jnl
Riemannian classification of EEG signals with missing values.
CoRR
Alexandre Hippert-Ferrer, Ammar Mian, Florent Bouchard, Frédéric Pascal
2020 — conf
A Riemannian approach to blind separation of t-distributed sources.
EUSIPCO
Florent Bouchard, Arnaud Breloy, Guillaume Ginolhac, Alexandre Renaux
2020 J jnl
Approximate Joint Diagonalization with Riemannian Optimization on the General Linear Group.
SIAM J. Matrix Anal. Appl.
Florent Bouchard, Bijan Afsari, Jérôme Malick, Marco Congedo
2020 Misc conf
Riemannian Framework for Robust Covariance Matrix Estimation in Spiked Models.
ICASSP
Florent Bouchard, Arnaud Breloy, Guillaume Ginolhac, Frédéric Pascal
2020 Misc conf
Riemannian Geometry and Cramér-rao Bound for Blind Separation of Gaussian Sources.
ICASSP
Florent Bouchard, Arnaud Breloy, Alexandre Renaux, Guillaume Ginolhac
2020 J jnl
Riemannian geometry for Compound Gaussian distributions: application to recursive change detection.
CoRR
Florent Bouchard, Ammar Mian, Jialun Zhou, Salem Said, Guillaume Ginolhac, Yannick Berthoumieu
2020 J jnl
Riemannian geometry for compound Gaussian distributions: Application to recursive change detection.
Signal Process.
Florent Bouchard, Ammar Mian, Jialun Zhou, Salem Said, Guillaume Ginolhac, Yannick Berthoumieu
2019 J jnl
Intrinsic Cramér-Rao Bounds for Scatter and Shape Matrices Estimation in CES Distributions.
IEEE Signal Process. Lett.
Arnaud Breloy, Guillaume Ginolhac, Alexandre Renaux, Florent Bouchard
2019 A* conf
Random Matrix Improved Covariance Estimation for a Large Class of Metrics.
ICML
Malik Tiomoko, Romain Couillet, Florent Bouchard, Guillaume Ginolhac
2019 J jnl
Random Matrix Improved Covariance Estimation for a Large Class of Metrics.
CoRR
Malik Tiomoko, Florent Bouchard, Guillaume Ginolhac, Romain Couillet
2018 — —
Géométrie et optimisation riemannienne pour la diagonalisation conjointe : application à la séparation de sources d'électroencéphalogrammes. (Riemannian geometry and optimization for approximate joint diagonalization : application to source separation of electroencephalograms).
Florent Bouchard
2018 J jnl
Riemannian Optimization and Approximate Joint Diagonalization for Blind Source Separation.
IEEE Trans. Signal Process.
Florent Bouchard, Jérôme Malick, Marco Congedo
2017 — conf
A closed-form unsupervised geometry-aware dimensionality reduction method in the Riemannian Manifold of SPD matrices.
EMBC
Marco Congedo, Pedro Luiz Coelho Rodrigues, Florent Bouchard, Alexandre Barachant, Christian Jutten
2017 — conf
Approximate Joint Diagonalization According to the Natural Riemannian Distance.
LVA/ICA
Florent Bouchard, Jérôme Malick, Marco Congedo
2017 — conf
Dimensionality Reduction for BCI Classification using Riemannian Geometry.
GBCIC
Pedro Luiz Coelho Rodrigues, Florent Bouchard, Marco Congedo, Christian Jutten
2016 — conf
Approximate joint diagonalization within the Riemannian geometry framework.
EUSIPCO
Florent Bouchard, Louis Korczowski, Jérôme Malick, Marco Congedo
2016 — conf
Mining the bilinear structure of data with approximate joint diagonalization.
EUSIPCO
Louis Korczowski, Florent Bouchard, Christian Jutten, Marco Congedo