An Interpolating Distance between Optimal Transport and Fisher-Rao
arXiv:1506.06430
Abstract
This paper defines a new transport metric over the space of non-negative measures. This metric interpolates between the quadratic Wasserstein and the Fisher-Rao metrics and generalizes optimal transport to measures with different masses. It is defined as a generalization of the dynamical formulation of optimal transport of Benamou and Brenier, by introducing a source term in the continuity equation. The influence of this source term is measured using the Fisher-Rao metric, and is averaged with the transportation term. This gives rise to a convex variational problem defining our metric. Our first contribution is a proof of the existence of geodesics (i.e. solutions to this variational problem). We then show that (generalized) optimal transport and Fisher-Rao metrics are obtained as limiting cases of our metric. Our last theoretical contribution is a proof that geodesics between mixtures of sufficiently close Diracs are made of translating mixtures of Diracs. Lastly, we propose a numerical scheme making use of first order proximal splitting methods and we show an application of this new distance to image interpolation.
References in corpus (3)
Cited by in corpus (10)
- Scaling Algorithms for Unbalanced Transport Problems
- Maximum Mean Discrepancy Gradient Flow
- Nonlinear model reduction on metric spaces. Application to one-dimensional conservative PDEs in Wasserstein spaces
- Indirect Image Registration with Large Diffeomorphic Deformations
- A JKO splitting scheme for Kantorovich-Fisher-Rao gradient flows
- Interpolation of Density Matrices and Matrix-Valued Measures: The Unbalanced Case
- A new multicomponent Poincaré-Beckner inequality
- Optimal Transport for Diffeomorphic Registration
- Regularity theory and geometry of unbalanced optimal transport
- A fitness-driven cross-diffusion system from polulation dynamics as a gradient flow