| Dimensionality Reduction for BCI classification using Riemannian geometry P Rodrigues, F Bouchard, M Congedo, C Jutten | 11 | 2017 |
| Intrinsic cramér–rao bounds for scatter and shape matrices estimation in ces distributions A Breloy, G Ginolhac, A Renaux, F Bouchard IEEE Signal Processing Letters 26 (2), 262-266, 2018 | 9 | 2018 |
| Riemannian optimization and approximate joint diagonalization for blind source separation F Bouchard, J Malick, M Congedo IEEE Transactions on Signal Processing 66 (8), 2041-2054, 2018 | 8 | 2018 |
| A closed-form unsupervised geometry-aware dimensionality reduction method in the Riemannian Manifold of SPD matrices M Congedo, PLC Rodrigues, F Bouchard, A Barachant, C Jutten 2017 39th Annual International Conference of the IEEE Engineering in …, 2017 | 6 | 2017 |
| Approximate joint diagonalization within the Riemannian geometry framework F Bouchard, L Korczowski, J Malick, M Congedo 2016 24th European Signal Processing Conference (EUSIPCO), 210-214, 2016 | 6 | 2016 |
| Approximate joint diagonalization according to the natural Riemannian distance F Bouchard, J Malick, M Congedo International Conference on Latent Variable Analysis and Signal Separation …, 2017 | 5 | 2017 |
| Mining the bilinear structure of data with approximate joint diagonalization L Korczowski, F Bouchard, C Jutten, M Congedo 2016 24th European Signal Processing Conference (EUSIPCO), 667-671, 2016 | 5 | 2016 |
| Random matrix improved covariance estimation for a large class of metrics M Tiomoko, F Bouchard, G Ginholac, R Couillet arXiv preprint arXiv:1902.02554, 2019 | 4 | 2019 |
| Approximate joint diagonalization with Riemannian optimization on the general linear group F Bouchard, B Afsari, J Malick, M Congedo SIAM Journal on Matrix Analysis and Applications 41 (1), 152-170, 2020 | 3 | 2020 |
| Géométrie Riemannienne appliquée à la réduction de la dimension de signaux EEG pour les interfaces cerveau-machine P Rodrigues, F Bouchard, M Congedo, C Jutten | 1 | 2017 |
| Réduction de dimension pour la Séparation Aveugle de Sources F Bouchard, P Rodrigues, J Malick, M Congedo | 1 | 2017 |
| Borne de Cramér-Rao intrinsèque pour la matrice de covariance des distributions elliptiques complexes A Breloy, A Renaux, G Ginolhac, F Bouchard | 1 | 2017 |
| Riemannian geometry for Compound Gaussian distributions: application to recursive change detection F Bouchard, A Mian, J Zhou, S Said, G Ginolhac, Y Berthoumieu arXiv preprint arXiv:2005.10087, 2020 | | 2020 |
| Riemannian Framework for Robust Covariance Matrix Estimation in Spiked Models F Bouchard, A Breloy, G Ginolhac, F Pascal ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | | 2020 |
| Riemannian Geometry and Cramér-rao Bound for Blind Separation of Gaussian Sources F Bouchard, A Breloy, A Renaux, G Ginolhac ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | | 2020 |
| A Riemannian Framework for Low-Rank Structured Elliptical Models F Bouchard, A Breloy, G Ginolhac, A Renaux, F Pascal arXiv preprint arXiv:2001.01141, 2020 | | 2020 |
| Bornes de Cramér-Rao Intrinseques pour l’estimation de la matrice de dispersion normalisée dans les distributions elliptiques F Bouchard, A Breloy, A Renaux, G Ginolhac GRETSI 2019, 2019 | | 2019 |
| Intrinsic Cramér-Rao Bounds for Scatter and Shape Matrices Estimation in Complex Elliptically Symmetric Distributions A Breloy, G Ginolhac, A Renaux, F Bouchard | | 2018 |
| Géométrie et optimisation riemannienne pour la diagonalisation conjointe: application à la séparation de sources d'électroencéphalogrammes F Bouchard | | 2018 |
| Extracting EEG sources of ERP based BCI by Composite Approximate Joint Diagonalization L Korczowski, F Bouchard, C Jutten, M Congedo | | 2018 |
