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The space of embedded submanifolds plays an important role in applications such as computational anatomy and shape analysis. We can define two different classes on Riemannian metrics on this space: so-called outer metrics are metrics that…

Differential Geometry · Mathematics 2017-09-19 Martins Bruveris

Reparametrization invariant Sobolev metrics on spaces of regular curves have been shown to be of importance in the field of mathematical shape analysis. For practical applications, one usually discretizes the space of smooth curves and…

Differential Geometry · Mathematics 2025-03-26 Jonathan Cerqueira , Emmanuel Hartman , Eric Klassen , Martin Bauer

The present document is the draft of a book which presents an introduction to infinite-dimensional differential geometry beyond Banach manifolds. As is well known the usual calculus breaks down in this setting. Hence, we replace it by the…

Differential Geometry · Mathematics 2023-03-09 Alexander Schmeding

Riemannian geometry provides the fundamental framework for optimization on nonlinear spaces such as matrix manifolds, which arise in machine learning, signal processing, and robotics. While the underlying theory is classical, existing…

Differential Geometry · Mathematics 2026-05-05 Benyamin Ghojogh

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 inter-disciplinary area of research with theoretical…

The analysis of manifold-valued data requires efficient tools from Riemannian geometry to cope with the computational complexity at stake. This complexity arises from the always-increasing dimension of the data, and the absence of…

Computer Vision and Pattern Recognition · Computer Science 2017-11-27 Maxime Louis , Alexandre Bône , Benjamin Charlier , Stanley Durrleman

Shape affects both the physical and chemical properties of a material. Characterizing the roughness, convexity, and general geometry of a material can yield information on its catalytic efficiency, solubility, elasticity, porosity, and…

Computational Engineering, Finance, and Science · Computer Science 2023-09-18 Alexander Smith , Steven Schilling , Prodromos Daoutidis

An algebraic formulation of Riemannian geometry on quantum spaces is presented, where Riemannian metric, distance, Laplacian, connection, and curvature have their counterparts. This description is also extended to complex manifolds.…

q-alg · Mathematics 2009-10-28 Pei-Ming Ho

This paper introduces a set of numerical methods for Riemannian shape analysis of 3D surfaces within the setting of invariant (elastic) second-order Sobolev metrics. More specifically, we address the computation of geodesics and geodesic…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Emmanuel Hartman , Yashil Sukurdeep , Eric Klassen , Nicolas Charon , Martin Bauer

These notes on Riemannian geometry use the bases bundle and frame bundle, as in Geometry of Manifolds, to express the geometric structures. It has more problems and omits the background material. It starts with the definition of Riemannian…

Differential Geometry · Mathematics 2013-07-30 Richard L. Bishop

A pedagogical but concise overview of Riemannian geometry is provided, in the context of usage in physics. The emphasis is on defining and visualizing concepts and relationships between them, as well as listing common confusions,…

General Relativity and Quantum Cosmology · Physics 2022-08-19 Adam Marsh

The Riemannian geometry is one of the main theoretical pieces in Modern Mathematics and Physics. The study of Riemann Geometry in the relevant literature is performed by using a well defined analytical path. Usually it starts from the…

Differential Geometry · Mathematics 2015-07-07 Juan Mendez

The differential-geometric structure of the manifold of smooth shapes is applied to the theory of shape optimization problems. In particular, a Riemannian shape gradient with respect to the first Sobolev metric and the Steklov-Poincar\'{e}…

Optimization and Control · Mathematics 2021-01-18 Kathrin Welker

Graphs are ubiquitous, and learning on graphs has become a cornerstone in artificial intelligence and data mining communities. Unlike pixel grids in images or sequential structures in language, graphs exhibit a typical non-Euclidean…

Machine Learning · Computer Science 2026-02-12 Li Sun , Qiqi Wan , Suyang Zhou , Zhenhao Huang , Philip S. Yu

Riemann surfaces are two-dimensional manifolds with a conformal class of metrics. It is well known that the harmonic action functional and harmonic maps are tools to study the moduli space of Riemann surfaces. Super Riemann surfaces are an…

Differential Geometry · Mathematics 2016-10-10 Enno Keßler

We explore the use of tools from Riemannian geometry for the analysis of symmetric positive definite matrices (SPD). An SPD matrix is a versatile data representation that is commonly used in chemical engineering (e.g.,…

Applications · Statistics 2022-03-24 Alexander Smith , Benjamin Laubach , Ivan Castillo , Victor M. Zavala

This is an overview article. In his Habilitationsvortrag, Riemann described infinite dimensional manifolds parameterizing functions and shapes of solids. This is taken as an excuse to describe convenient calculus in infinite dimensions…

Differential Geometry · Mathematics 2016-04-08 Peter W. Michor

In the recent years, Riemannian shape analysis of curves and surfaces has found several applications in medical image analysis. In this paper we present a numerical discretization of second order Sobolev metrics on the space of regular…

Differential Geometry · Mathematics 2015-07-01 Martin Bauer , Martins Bruveris , Philipp Harms , Jakob Møller-Andersen

This article provides an overview of various notions of shape spaces, including the space of parametrized and unparametrized curves, the space of immersions, the diffeomorphism group and the space of Riemannian metrics. We discuss the…

Differential Geometry · Mathematics 2014-10-07 Martin Bauer , Martins Bruveris , Peter W. Michor

We present a Riemannian framework for linear and quadratic discriminant classification on the tangent plane of the shape space of curves. The shape space is infinite dimensional and is constructed out of square root velocity functions of…

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