Name
Abstract | ||
|---|---|---|
In this article we explore an algorithm for diffeomorphic random sampling of nonuniform probability distributions on Riemannian manifolds. The algorithm is based on optimal information transport (OIT)-an analogue of optimal mass transport (OMT). Our framework uses the deep geometric connections between the Fisher-Rao metric on the space of probability densities and the right-invariant information metric on the group of diffeomorphisms. The resulting sampling algorithm is a promising alternative to OMT, in particular as our formulation is semi-explicit, free of the nonlinear Monge-Ampere equation. Compared to Markov Chain Monte Carlo methods, we expect our algorithm to stand up well when a large number of samples from a low dimensional nonuniform distribution is needed. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/978-3-319-68445-1_16 | GEOMETRIC SCIENCE OF INFORMATION, GSI 2017 |
Keywords | Field | DocType |
Density matching, Information geometry, Fisher-Rao metric, Optimal transport, Image registration, Diffeomorphism groups, Random sampling | Information geometry,Discrete mathematics,Applied mathematics,Mathematical optimization,Nonlinear system,Markov chain Monte Carlo,Computer science,Probability distribution,Sampling (statistics),Manifold,Image registration,Diffeomorphism | Conference |
Volume | ISSN | Citations |
10589 | 0302-9743 | 1 |
PageRank | References | Authors |
0.36 | 2 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Martin Bauer | 1 | 52 | 10.45 |
| Sarang Joshi | 2 | 1351 | 95.22 |
| Klas Modin | 3 | 13 | 4.22 |