Isometric Embedding of Riemannian Manifolds in Euclidean Spaces, 2006. ,
DOI : 10.1090/surv/130
Intrinsic loss functions, Theory and Decision, vol.40, pp.192-214, 1996. ,
Integrated Objective Bayesian Estimation and Hypothesis Testing, Bayesian statistics 9, 2010. ,
DOI : 10.1093/acprof:oso/9780199694587.003.0001
Covariance, subspace, and intrinsic Crame/spl acute/r-Rao bounds, IEEE Transactions on Signal Processing, vol.53, issue.5, pp.1610-1630, 2005. ,
DOI : 10.1109/TSP.2005.845428
Information geometry and prior selection, AIP Conference Proceedings, 2002. ,
DOI : 10.1063/1.1570549
Intrinsic Statistics on Riemannian Manifolds: Basic Tools for Geometric Measurements, Journal of Mathematical Imaging and Vision, vol.20, issue.10, pp.127-154, 2006. ,
DOI : 10.1007/s10851-006-6228-4
URL : https://hal.archives-ouvertes.fr/inria-00614994
Statistics on the Manifold of Multivariate Normal Distributions: Theory and Application to Diffusion Tensor MRI Processing, Journal of Mathematical Imaging and Vision, vol.12, issue.1, pp.423-444, 2006. ,
DOI : 10.1007/s10851-006-6897-z
Approximate Bayesian Inference in Conditionally Independent Hierarchical Models (Parametric Empirical Bayes Models), Journal of the American Statistical Association, vol.84, issue.407, pp.717-726, 1989. ,
DOI : 10.1080/01621459.1989.10478825
Fully Exponential Laplace Approximations Using Asymptotic Modes, Journal of the American Statistical Association, vol.99, issue.468, pp.1037-1049, 2004. ,
DOI : 10.1198/016214504000001673
An Asymptotic Expansion for Posterior Distributions, The Annals of Mathematical Statistics, vol.38, issue.6, pp.1899-1906, 1967. ,
DOI : 10.1214/aoms/1177698624
Natural Gradient Works Efficiently in Learning, Neural Computation, vol.37, issue.2, pp.251-276, 1998. ,
DOI : 10.1103/PhysRevLett.76.2188
Information-geometric optimization algorithms: A unifying picture via invariance principles, 2011. ,
URL : https://hal.archives-ouvertes.fr/hal-00601503
Multivariate statistical modeling for texture analysis using wavelet transforms Centroidbased texture classification using the SIRV representation, IEEE International Conference on Acoustics Speech and Signal Processing IEEE International Conference on Image Processing, pp.790-793, 2010. ,
Supervised Texture Classification Using Characteristic Generalized Gaussian Density, Journal of Mathematical Imaging and Vision, vol.2, issue.4, pp.35-47, 2007. ,
DOI : 10.1007/s10851-007-0023-8
Kcentroids based supervised classification of texture images: handling the intra-class diversity, IEEE International Conference on Acoustics, Speech, and Signal Processing, pp.1498-1502, 2013. ,
URL : https://hal.archives-ouvertes.fr/hal-00841939
Multivariate texture discrimination based on geodesics to class centroids on a generalized Gaussian manifold Geometric Science of information, pp.853-860, 2013. ,
A Coefficient of Agreement for Nominal Scales, Educational and Psychological Measurement, vol.20, issue.1, pp.37-46, 1960. ,
DOI : 10.1177/001316446002000104
Determining the accuracy in image supervised classification problems, Proceedings of the 7th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-2011), pp.342-349, 2011. ,
DOI : 10.2991/eusflat.2011.103