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Learning the spatiotemporal variability in longitudinal shape data sets., , and . Int. J. Comput. Vis., 128 (12): 2873-2896 (2020)A Fanning Scheme for the Parallel Transport along Geodesics on Riemannian Manifolds., , , , and . SIAM J. Numer. Anal., 56 (4): 2563-2584 (2018)Predicting PET-derived myelin content from multisequence MRI for individual longitudinal analysis in multiple sclerosis., , , , , , , and . NeuroImage, (2020)A Sub-Riemannian Modular Framework for Diffeomorphism-Based Analysis of Shape Ensembles., , and . SIAM J. Imaging Sci., 11 (1): 802-833 (2018)Transporting Deformations of Face Emotions in the Shape Spaces: A Comparison of Different Approaches., , , , , , , and . J. Math. Imaging Vis., 63 (7): 875-893 (2021)Benchmarking off-the-shelf statistical shape modeling tools in clinical applications., , , , , , , , , and 1 other author(s). CoRR, (2020)Simulation of virtual cohorts increases predictive accuracy of cognitive decline in MCI subjects., , and . CoRR, (2019)Mixture of Conditional Gaussian Graphical Models for Unlabelled Heterogeneous Populations in the Presence of Co-factors., , and . SN Comput. Sci., 2 (6): 466 (2021)Progression Models for Imaging Data with Longitudinal Variational Auto Encoders., and . MICCAI (1), volume 13431 of Lecture Notes in Computer Science, page 3-13. Springer, (2022)Learning Joint Shape and Appearance Representations with Metamorphic Auto-Encoders., , , and . MICCAI (1), volume 12261 of Lecture Notes in Computer Science, page 202-211. Springer, (2020)