activity
20072025
most citedSinkhorn Divergences for Unbalanced Optimal Transport

44 citations · 50 across the 5 of their papers we have counts for

collaborators

8 papers

math.DG2025

Barycentric subspace analysis of network-valued data

Elodie Maignant, Xavier Pennec, Alain Trouvé +1

Certain data are naturally modeled by networks or weighted graphs, be they biological networks or mobility networks. When there is no canonical labeling of the nodes across the dat…

math.NA2022★ 3 cited

Image Varifolds on Meshes for Mapping Spatial Transcriptomics

Michael I Miller, Alain Trouvé, Laurent Younes

Advances in the development of largely automated microscopy methods such as MERFISH for imaging cellular structures in mouse brains are providing spatial detection of micron resolu…

math.DG2021

Parallel Transport on Kendall Shape Spaces

Nicolas Guigui, Elodie Maignant, Alain Trouvé +1

Kendall shape spaces are a widely used framework for the statistical analysis of shape data arising from many domains, often requiring the parallel transport as a tool to normalise…

math.OC2019★ 44 cited

Sinkhorn Divergences for Unbalanced Optimal Transport

Thibault Séjourné, Jean Feydy, François-Xavier Vialard +2

Optimal transport induces the Earth Mover's (Wasserstein) distance between probability distributions, a geometric divergence that is relevant to a wide range of problems. Over the…

math.OC2015★ 3 cited

Multiple Shape Registration using Constrained Optimal Control

Sylvain Arguillère, Emmanuel Trélat, Alain Trouvé +1

Lagrangian particle formulations of the large deformation diffeomorphic metric mapping algorithm (LDDMM) only allow for the study of a single shape. In this paper, we introduce and…

math.OC2014

Shape deformation analysis from the optimal control viewpoint

Sylvain Arguillere, Emmanuel Trélat, Alain Trouvé +1

A crucial problem in shape deformation analysis is to determine a deformation of a given shape into another one, which is optimal for a certain cost. It has a number of application…