Hodge Theory on Metric Spaces

12/01/2009
by   Laurent Bartholdi, et al.
0

Hodge theory is a beautiful synthesis of geometry, topology, and analysis, which has been developed in the setting of Riemannian manifolds. On the other hand, spaces of images, which are important in the mathematical foundations of vision and pattern recognition, do not fit this framework. This motivates us to develop a version of Hodge theory on metric spaces with a probability measure. We believe that this constitutes a step towards understanding the geometry of vision. The appendix by Anthony Baker provides a separable, compact metric space with infinite dimensional α-scale homology.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
12/06/2020

A Lecture About the Use of Orlicz Spaces in Information Geometry

This is a revised version of a tutorial lecture that I presented at the ...
research
10/25/2018

Geometry and clustering with metrics derived from separable Bregman divergences

Separable Bregman divergences induce Riemannian metric spaces that are i...
research
01/03/2018

Differential Geometry for Model Independent Analysis of Images and Other Non-Euclidean Data: Recent Developments

This article provides an exposition of recent methodologies for nonparam...
research
05/06/2021

A Unifying and Canonical Description of Measure-Preserving Diffusions

A complete recipe of measure-preserving diffusions in Euclidean space wa...
research
12/12/2020

Sparsifying networks by traversing Geodesics

The geometry of weight spaces and functional manifolds of neural network...
research
10/31/2022

Statistical properties of approximate geometric quantiles in infinite-dimensional Banach spaces

Geometric quantiles are location parameters which extend classical univa...
research
06/30/2016

Ordering as privileged information

We propose to accelerate the rate of convergence of the pattern recognit...

Please sign up or login with your details

Forgot password? Click here to reset