On a Lagrangian Reduction and a Deformation of Completely Integrable Systems. - Alexis Arnaudon (J. Nonlinear Sci., 2016)

A Stochastic Large Deformation Model for Computational Anatomy. - Alexis Arnaudon; Darryl D. Holm; Akshay Pai; Stefan Sommer (IPMI, 2017)

Bridge Simulation and Metric Estimation on Landmark Manifolds. - Stefan Sommer; Alexis Arnaudon; Line Kühnel; Sarang C. Joshi (GRAIL/MFCA/MICGen@MICCAI, 2017)

Stochastic metamorphosis with template uncertainties. - Alexis Arnaudon; Darryl D. Holm; Stefan Sommer (CoRR, 2017)

Stochastic Image Deformation in Frequency Domain and Parameter Estimation using Moment Evolutions. - Line Kühnel; Alexis Arnaudon; Tom Fletcher; Stefan Sommer (CoRR, 2018)

String Methods for Stochastic Image and Shape Matching. - Alexis Arnaudon; Darryl D. Holm; Stefan Sommer (J. Math. Imaging Vis., 2018)

Noise and Dissipation on Coadjoint Orbits. - Alexis Arnaudon; Alex L. De Castro; Darryl D. Holm (J. Nonlinear Sci., 2018)

Irreversible Langevin MCMC on Lie Groups. - Alexis Arnaudon; Alessandro Barp; So Takao (GSI, 2019)

Selective Metamorphosis for Growth Modelling with Applications to Landmarks. - Andreas A. Bock; Alexis Arnaudon; Colin J. Cotter (GSI, 2019)

Differential geometry and stochastic dynamics with deep learning numerics. - Line Kühnel; Stefan Sommer; Alexis Arnaudon (Appl. Math. Comput., 2019)

Graph centrality is a question of scale. - Alexis Arnaudon; Robert L. Peach; Mauricio Barahona (CoRR, 2019)

Semi-supervised classification on graphs using explicit diffusion dynamics. - Robert L. Peach; Alexis Arnaudon; Mauricio Barahona (CoRR, 2019)

A Geometric Framework for Stochastic Shape Analysis. - Alexis Arnaudon; Darryl D. Holm; Stefan Sommer (Found. Comput. Math., 2019)

Diffusion bridges for stochastic Hamiltonian systems with applications to shape analysis. - Alexis Arnaudon; Frank van der Meulen; Moritz Schauer; Stefan Sommer (CoRR, 2020)

Unfolding the multiscale structure of networks with dynamical Ollivier-Ricci curvature. - Adam Gosztolai; Alexis Arnaudon (CoRR, 2021)

HCGA: Highly comparative graph analysis for network phenotyping. - Robert L. Peach; Alexis Arnaudon; Julia A. Schmidt; Henry A. Palasciano; Nathan R. Bernier; Kim E. Jelfs; Sophia N. Yaliraki; Mauricio Barahona (Patterns, 2021)

Diffusion Bridges for Stochastic Hamiltonian Systems and Shape Evolutions. - Alexis Arnaudon; Frank van der Meulen; Moritz Schauer; Stefan Sommer (SIAM J. Imaging Sci., 2022)

PyGenStability: Multiscale community detection with generalized Markov Stability. - Alexis Arnaudon; Dominik J. Schindler; Robert L. Peach; Adam Gosztolai; Maxwell Hodges; Michael T. Schaub; Mauricio Barahona (CoRR, 2023)

Interpretable statistical representations of neural population dynamics and geometry. - Adam Gosztolai; Robert L. Peach; Alexis Arnaudon; Mauricio Barahona; Pierre Vandergheynst (CoRR, 2023)

Moment Evolution Equations and Moment Matching for Stochastic Image EPDiff. - Alexander Mangulad Christgau; Alexis Arnaudon; Stefan Sommer (J. Math. Imaging Vis., 2023)

A universal workflow for creation, validation, and generalization of detailed neuronal models. - Maria Reva; Christian Rössert; Alexis Arnaudon; Tanguy Damart; Darshan Mandge; Anil Tuncel; Srikanth Ramaswamy; Henry Markram; Werner Van Geit (Patterns, 2023)

Algorithm 1044: PyGenStability, a Multiscale Community Detection Framework with Generalized Markov Stability. - Alexis Arnaudon; Dominik J. Schindler; Robert L. Peach; Adam Gosztolai; Maxwell Hodges; Michael T. Schaub; Mauricio Barahona (ACM Trans. Math. Softw., 2024)