3 citations · 3 across the 3 of their papers we have counts for
6 papers
Approximation of Riemannian Distances and Applications to Distance-Based Learning on Manifolds
Philipp Harms, Elodie Maignant, Stefan Schlager
Several important algorithms for machine learning and data analysis use pairwise distances as input. On Riemannian manifolds these distances may be prohibitively costly to compute,…
Inexact elastic shape matching in the square root normal field framework
Martin Bauer, Nicolas Charon, Philipp Harms
This paper puts forth a new formulation and algorithm for the elastic matching problem on unparametrized curves and surfaces. Our approach combines the frameworks of square root no…
Math in the Black Forest: Workshop on New Directions in Shape Analysis
Martin Bauer, Nicolas Charon, Philipp Harms +9
These are the proceedings of the workshop "Math in the Black Forest", which brought together researchers in shape analysis to discuss promising new directions. Shape analysis is an…
Vanishing distance phenomena and the geometric approach to SQG
Martin Bauer, Philipp Harms, Stephen C. Preston
In this article we study the induced geodesic distance of fractional order Sobolev metrics on the groups of (volume preserving) diffeomorphisms and symplectomorphisms. The interest…
The Poincaré Lemma in Subriemannian Geometry
Philipp Harms
This work is a short, self-contained introduction to subriemannian geometry with special emphasis on Chow's Theorem. As an application, a regularity result for the Poincaré Lemma i…
Sobolev metrics on shape space of surfaces
Philipp Harms
Many procedures in science, engineering and medicine produce data in the form of geometric shapes. Mathematically, a shape can be modeled as an un-parameterized immersed sub-manifo…