F. Beg, M. Miller, A. Trouvé, and L. Younes, Computing large deformation metric mappings via geodesic flows of diffeomorphisms, IJCV, 2005.

A. V. Dalca, G. Balakrishnan, J. Guttag, and M. R. Sabuncu, Unsupervised learning for fast probabilistic diffeomorphic registration, 2018.

S. Durrleman, Statistical models of currents for measuring the variability of anatomical curves, surfaces and their evolution, 2010.
URL : https://hal.archives-ouvertes.fr/tel-00631382

S. Durrleman, M. Prastawa, N. Charon, J. R. Korenberg, S. Joshi et al., Morphometry of anatomical shape complexes with dense deformations and sparse parameters, NeuroImage, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01015771

P. Gori, O. Colliot, L. Marrakchi-kacem, Y. Worbe, C. Poupon et al., A bayesian framework for joint morphometry of surface and curve meshes in multi-object complexes, Medical Image Analysis, vol.35, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01359423

B. Gris, S. Durrleman, and A. Trouvé, A sub-riemannian modular framework for diffeomorphism-based analysis of shape ensembles, SIAM Journal on Imaging Sciences, vol.11, issue.1, pp.802-833, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01321142

M. I. Jordan, Z. Ghahramani, T. S. Jaakkola, and L. K. Saul, An introduction to variational methods for graphical models, Machine learning, vol.37, issue.2, pp.183-233, 1999.

D. P. Kingma and M. Welling, Auto-encoding variational bayes, stat, vol.1050, p.10, 2014.

M. I. Miller, A. Trouvé, and L. Younes, Geodesic shooting for computational anatomy, Journal of Mathematical Imaging and Vision, vol.24, issue.2, pp.209-228, 2006.

A. Paszke, S. Gross, S. Chintala, G. Chanan, E. Yang et al., Automatic differentiation in pytorch, 2017.

X. Pennec, Intrinsic statistics on riemannian manifolds: Basic tools for geometric measurements, Journal of Mathematical Imaging and Vision, vol.25, issue.1, pp.127-154, 2006.
URL : https://hal.archives-ouvertes.fr/inria-00614994

D. W. Thompson, On growth and form. On growth and form, 1942.

M. Vaillant and J. Glaunès, Surface matching via currents. In: Information processing in medical imaging, pp.1-5, 2005.
URL : https://hal.archives-ouvertes.fr/hal-00263652

T. Vercauteren, X. Pennec, A. Perchant, and N. Ayache, Symmetric log-domain diffeomorphic registration: A demons-based approach, 2008.
URL : https://hal.archives-ouvertes.fr/inria-00280602

X. Yang, R. Kwitt, M. Styner, and M. Niethammer, Quicksilver: Fast predictive image registration-a deep learning approach, NeuroImage, vol.158, pp.378-396, 2017.

L. Younes, Shapes and Diffeomorphisms. Applied Mathematical Sciences, 2010.

M. Zhang and P. T. Fletcher, Bayesian principal geodesic analysis in diffeomorphic image registration, International Conference on Medical Image Computing and Computer-Assisted Intervention, pp.121-128, 2014.

M. Zhang and P. T. Fletcher, Fast diffeomorphic image registration via fourierapproximated lie algebras, Int. Journal of Computer Vision, pp.1-13, 2018.