X. Pennec, P. Fillard, and N. Ayache, A Riemannian Framework for Tensor Computing, International Journal of Computer Vision, vol.6, issue.2, pp.41-66, 2006.
DOI : 10.1016/S0925-7721(01)00018-9

URL : https://hal.archives-ouvertes.fr/inria-00070743

A. Barachant, S. Bonnet, M. Congedo, and C. Jutten, Multiclass Brain–Computer Interface Classification by Riemannian Geometry, IEEE Transactions on Biomedical Engineering, vol.59, issue.4, pp.920-928, 2012.
DOI : 10.1109/TBME.2011.2172210

M. Arnaudon, F. Barbaresco, and L. Yang, Riemannian Medians and Means With Applications to Radar Signal Processing, IEEE Journal of Selected Topics in Signal Processing, vol.7, issue.4, pp.595-604, 2013.
DOI : 10.1109/JSTSP.2013.2261798

O. Tuzel, F. Porikli, and P. Meer, Pedestrian Detection via Classification on Riemannian Manifolds, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.30, issue.10, pp.1731-1727, 2008.
DOI : 10.1109/TPAMI.2008.75

URL : http://www.merl.com/reports/docs/TR2008-037.pdf

G. Dong and G. Kuang, Target recognition in sar images via classification on riemannian manifolds, IEEE Geoscie. Remote Sens. Lett, vol.21, issue.1, pp.199-203, 2015.

S. Said, L. Bombrun, Y. Berthoumieu, and J. H. Manton, Riemannian Gaussian Distributions on the Space of Symmetric Positive Definite Matrices, IEEE Transactions on Information Theory, vol.63, issue.4, pp.2153-2170, 2017.
DOI : 10.1109/TIT.2017.2653803

S. Said, L. Bombrun, and Y. Berthoumieu, Texture classification using Rao's distance: An EM algorithm on the poincaré half plane, 2015 IEEE International Conference on Image Processing (ICIP), 2015.
DOI : 10.1109/ICIP.2015.7351448

P. Zanini, M. Congedo, C. Jutten, S. Said, and Y. Berthomieu, Parameters estimate of Riemannian Gaussian distribution in the manifold of covariance matrices, 2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), 2016.
DOI : 10.1109/SAM.2016.7569687

URL : https://hal.archives-ouvertes.fr/hal-01325055

D. Titterington, Recursive parameter estimation using incomplete data, Journal of the Royal Statistical Society Series B (Statistical Methodologies), vol.46, issue.2, pp.257-267, 1984.
DOI : 10.21236/ADA116190

O. Cappé and E. Moulines, Online em algorithm for latent data models, Journal of the Royal Statistical Society Series B (Statistical Methodologies), pp.593-613, 2009.

S. Helgason, Differential Geometry, Lie Groups, and Symmetric Space, 2012.
DOI : 10.1090/gsm/034

S. Said and Y. Berthoumieu, Warped Metrics for Location-Scale Models, 2017.
DOI : 10.1007/978-3-642-18855-8

S. Said, H. Hajri, L. Bombrun, and B. Vemuri, Gaussian distributions on Riemannian symmetric spaces : statistical learning with structured covariance matrices, IEEE Transactions on Information Theory, 2016.
DOI : 10.1109/TIT.2017.2713829