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ORCIDFlorent Bouchard
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Books and Theses
- 2018
[b1]Florent Bouchard:
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). Grenoble Alpes University, France, 2018
Journal Articles
- 2024
- [j8]Ammar Mian
, Guillaume Ginolhac, Florent Bouchard, Arnaud Breloy:
Online change detection in SAR time-series with Kronecker product structured scaled Gaussian models. Signal Process. 224: 109589 (2024) - [j7]Florent Bouchard, Alexandre Renaux, Guillaume Ginolhac, Arnaud Breloy:
Intrinsic Bayesian Cramér-Rao Bound With an Application to Covariance Matrix Estimation. IEEE Trans. Inf. Theory 70(12): 9261-9276 (2024) - 2021
- [j6]Florent Bouchard, Arnaud Breloy, Guillaume Ginolhac, Alexandre Renaux, Frédéric Pascal:
A Riemannian Framework for Low-Rank Structured Elliptical Models. IEEE Trans. Signal Process. 69: 1185-1199 (2021) - [j5]Antoine Collas, Florent Bouchard, Arnaud Breloy, Guillaume Ginolhac, Chengfang Ren, Jean Philippe Ovarlez:
Probabilistic PCA From Heteroscedastic Signals: Geometric Framework and Application to Clustering. IEEE Trans. Signal Process. 69: 6546-6560 (2021) - 2020
- [j4]Florent Bouchard, Bijan Afsari, Jérôme Malick, Marco Congedo:
Approximate Joint Diagonalization with Riemannian Optimization on the General Linear Group. SIAM J. Matrix Anal. Appl. 41(1): 152-170 (2020) - [j3]Florent Bouchard, Ammar Mian, Jialun Zhou, Salem Said, Guillaume Ginolhac, Yannick Berthoumieu:
Riemannian geometry for compound Gaussian distributions: Application to recursive change detection. Signal Process. 176: 107716 (2020) - 2019
- [j2]Arnaud Breloy, Guillaume Ginolhac, Alexandre Renaux, Florent Bouchard:
Intrinsic Cramér-Rao Bounds for Scatter and Shape Matrices Estimation in CES Distributions. IEEE Signal Process. Lett. 26(2): 262-266 (2019) - 2018
- [j1]Florent Bouchard, Jérôme Malick, Marco Congedo:
Riemannian Optimization and Approximate Joint Diagonalization for Blind Source Separation. IEEE Trans. Signal Process. 66(8): 2041-2054 (2018)
Conference and Workshop Papers
- 2024
- [c19]Thu Ha Phi, Alexandre Hippert-Ferrer, Florent Bouchard, Arnaud Breloy:
Leveraging Standardization in Graph Learning. EUSIPCO 2024: 2492-2496 - [c18]Thu Ha Phi, Alexandre Hippert-Ferrer, Florent Bouchard, Arnaud Breloy:
Robust Low-Rank Correlation Fitting. ICASSP 2024: 9416-9420 - [c17]Florent Bouchard, Ammar Mian, Malik Tiomoko, Guillaume Ginolhac, Frédéric Pascal:
Random matrix theory improved Fréchet mean of symmetric positive definite matrices. ICML 2024 - 2023
- [c16]Imen Ayadi, Florent Bouchard, Frédéric Pascal:
t-WDA: A novel Discriminant Analysis applied to EEG classification. EUSIPCO 2023: 1793-1797 - [c15]Imen Ayadi, Florent Bouchard, Frédéric Pascal:
Elliptical Wishart Distribution: Maximum Likelihood Estimator from Information Geometry. ICASSP 2023: 1-5 - [c14]Alexandre Hippert-Ferrer, Florent Bouchard, Ammar Mian, Titouan Vayer, Arnaud Breloy:
Learning Graphical Factor Models with Riemannian Optimization. ECML/PKDD (4) 2023: 349-366 - 2022
- [c13]Alexandre Hippert-Ferrer, Ammar Mian, Florent Bouchard, Frédéric Pascal:
Riemannian Classification of EEG Signals with Missing Values. EUSIPCO 2022: 842-846 - [c12]Antoine Collas, Florent Bouchard, Guillaume Ginolhac, Arnaud Breloy, Chengfang Ren, Jean Philippe Ovarlez:
On the Use of Geodesic Triangles between Gaussian Distributions for Classification Problems. ICASSP 2022: 5697-5701 - 2021
- [c11]Florent Bouchard, Arnaud Breloy, Ammar Mian, Guillaume Ginolhac:
On-line Kronecker Product Structured Covariance Estimation with Riemannian geometry for t-distributed data. EUSIPCO 2021: 856-859 - [c10]Antoine Collas, Florent Bouchard, Arnaud Breloy, Chenfang Ren, Guillaume Ginolhac, Jean Philippe Ovarlez:
A Tyler-Type Estimator of Location and Scatter Leveraging Riemannian Optimization. ICASSP 2021: 5160-5164 - 2020
- [c9]Florent Bouchard, Arnaud Breloy, Guillaume Ginolhac, Alexandre Renaux:
A Riemannian approach to blind separation of t-distributed sources. EUSIPCO 2020: 965-969 - [c8]Florent Bouchard, Arnaud Breloy, Alexandre Renaux, Guillaume Ginolhac:
Riemannian Geometry and Cramér-rao Bound for Blind Separation of Gaussian Sources. ICASSP 2020: 4717-4721 - [c7]Florent Bouchard, Arnaud Breloy, Guillaume Ginolhac, Frédéric Pascal:
Riemannian Framework for Robust Covariance Matrix Estimation in Spiked Models. ICASSP 2020: 5979-5983 - 2019
- [c6]Malik Tiomoko, Romain Couillet, Florent Bouchard, Guillaume Ginolhac:
Random Matrix Improved Covariance Estimation for a Large Class of Metrics. ICML 2019: 6254-6263 - 2017
- [c5]Marco Congedo, Pedro Luiz Coelho Rodrigues, Florent Bouchard, Alexandre Barachant, Christian Jutten:
A closed-form unsupervised geometry-aware dimensionality reduction method in the Riemannian Manifold of SPD matrices. EMBC 2017: 3198-3201 - [c4]Pedro Luiz Coelho Rodrigues, Florent Bouchard, Marco Congedo, Christian Jutten:
Dimensionality Reduction for BCI Classification using Riemannian Geometry. GBCIC 2017 - [c3]Florent Bouchard, Jérôme Malick, Marco Congedo:
Approximate Joint Diagonalization According to the Natural Riemannian Distance. LVA/ICA 2017: 290-299 - 2016
- [c2]Florent Bouchard, Louis Korczowski, Jérôme Malick, Marco Congedo:
Approximate joint diagonalization within the Riemannian geometry framework. EUSIPCO 2016: 210-214 - [c1]Louis Korczowski, Florent Bouchard, Christian Jutten, Marco Congedo:
Mining the bilinear structure of data with approximate joint diagonalization. EUSIPCO 2016: 667-671
Informal and Other Publications
- 2024
- [i8]Florent Bouchard, Ammar Mian, Malik Tiomoko, Guillaume Ginolhac, Frédéric Pascal:
Random matrix theory improved Fréchet mean of symmetric positive definite matrices. CoRR abs/2405.06558 (2024) - [i7]Imen Ayadi, Florent Bouchard, Frédéric Pascal:
Elliptical Wishart distributions: information geometry, maximum likelihood estimator, performance analysis and statistical learning. CoRR abs/2411.02726 (2024) - 2023
- [i6]Florent Bouchard, Arnaud Breloy, Antoine Collas, Alexandre Renaux, Guillaume Ginolhac:
The Fisher-Rao geometry of CES distributions. CoRR abs/2310.01032 (2023) - [i5]Florent Bouchard, Alexandre Renaux, Guillaume Ginolhac, Arnaud Breloy:
Natural Bayesian Cramér-Rao Bound with an Application to Covariance Estimation. CoRR abs/2311.04748 (2023) - 2022
- [i4]Alexandre Hippert-Ferrer, Florent Bouchard, Ammar Mian, Titouan Vayer, Arnaud Breloy:
Learning Graphical Factor Models with Riemannian Optimization. CoRR abs/2210.11950 (2022) - 2021
- [i3]Alexandre Hippert-Ferrer, Ammar Mian, Florent Bouchard, Frédéric Pascal:
Riemannian classification of EEG signals with missing values. CoRR abs/2110.10011 (2021) - 2020
- [i2]Florent Bouchard, Ammar Mian, Jialun Zhou, Salem Said, Guillaume Ginolhac, Yannick Berthoumieu:
Riemannian geometry for Compound Gaussian distributions: application to recursive change detection. CoRR abs/2005.10087 (2020) - 2019
- [i1]Malik Tiomoko, Florent Bouchard, Guillaume Ginolhac, Romain Couillet:
Random Matrix Improved Covariance Estimation for a Large Class of Metrics. CoRR abs/1902.02554 (2019)
Coauthor Index
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