The shape space defined by the Gromov- Wasserstein distance

Facundo Mémoli

( Ohio State University)

Event: ERC Workshop on Optimal Transportation and Applications

Date: Oct 28, 2014, time: 12:10

Abstract. In a number of applications, datasets or shapes can be modeled as metric
measure spaces. The Gromov-Wasserstein distance –a variant of the Gromov-Hausdorff
distance based on ideas from mass transport– provides an intrinsic metric on the collection of all mm-spaces. I will review its construction, main properties, lower bounds, and computation.