Learning the clustering of longitudinal shape data sets into a mixture of independent or branching trajectories V Debavelaere, S Durrleman, S Allassonnière, ... International Journal of Computer Vision 128 (12), 2794-2809, 2020 | 24 | 2020 |
On the curved exponential family in the stochastic approximation expectation maximization algorithm V Debavelaere, S Allassonnière ESAIM: Probability and Statistics 25, 408-432, 2021 | 13 | 2021 |
On the convergence of stochastic approximations under a subgeometric ergodic Markov dynamic V Debavelaere, S Durrleman, S Allassonnière Electronic Journal of Statistics 15 (1), 1583-1609, 2021 | 12 | 2021 |
Clustering of longitudinal shape data sets using mixture of separate or branching trajectories V Debavelaere, A Bône, S Durrleman, S Allassonnière, ... International Conference on Medical Image Computing and Computer-Assisted …, 2019 | 11 | 2019 |
A coherent framework for learning spatiotemporal piecewise-geodesic trajectories from longitudinal manifold-valued data J Chevallier, V Debavelaere, S Allassonniere SIAM Journal on Imaging Sciences 14 (1), 349-388, 2021 | 5 | 2021 |
Statistical modelling of medical data and theoretical analysis of estimation algorithms V Debavelaere Institut Polytechnique de Paris, 2021 | | 2021 |
Modélisation statistique de données médicales et analyse théorique des algorithmes d’estimation V Debavelaere Institut polytechnique de Paris, 2021 | | 2021 |
On the curved exponential family in the Stochatic Approximation Expectation Maximization Algorithm-Supplementary material V Debavelaere, S Allassonniere | | |