1 citations · 1 across the 4 of their papers we have counts for
5 papers
Stochastic Completeness for Landmark Shape Spaces with Induced Metrics
Karen Habermann, Mao Nishino, Stefan Sommer
Landmark shape spaces arise from configurations of distinct landmarks with rigid motions factored out and scale normalized. When equipped with sufficiently regular metrics inhe…
Metric Geometry of Lebesgue, Wasserstein, and Gromov-Wasserstein Spaces: Submetries, Curvature, and Geodesics
Martin Bauer, Facundo Mémoli, Tom Needham +1
A metric space gives rise to three natural classes of infinite-dimensional metric spaces associated to : -Wasserstein spaces of probability measures on , nonlinear Leb…
A Benamou-Brenier Proximal Splitting Method for Constrained Unbalanced Optimal Transport
Mao Nishino, Martin Bauer, Tom Needham +1
The dynamic formulation of optimal transport, also known as the Benamou-Brenier formulation, has been extended to the unbalanced case by introducing a source term in the continuity…
The Z-Gromov-Wasserstein Distance
Martin Bauer, Facundo Mémoli, Tom Needham +1
The Gromov-Wasserstein (GW) distance is a powerful tool for comparing metric measure spaces which has found broad applications in data science and machine learning. Driven by the n…
Path constrained unbalanced optimal transport
Martin Bauer, Nicolas Charon, Tom Needham +1
Dynamical formulations of optimal transport (OT) frame the task of comparing distributions as a variational problem which searches for a path between distributions minimizing a kin…