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Related papers: Towards Riemannian diffeology

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Motivated by a paper of Zirnbauer, we develop a theory of Riemannian supermanifolds up to a definition of Riemannian symmetric superspaces. Various fundamental concepts needed for the study of these spaces both from the Riemannian and the…

Differential Geometry · Mathematics 2009-08-12 Oliver Goertsches

Approximating a manifold-valued function from samples of input-output pairs consists of modeling the relationship between an input from a vector space and an output on a Riemannian manifold. We propose a function approximation method that…

Numerical Analysis · Mathematics 2025-04-18 Hang Wang , Raf Vandebril , Joeri Van der Veken , Nick Vannieuwenhoven

This is the author's Ph.D. thesis, submitted to the University of Leipzig. It deals with the $L^2$ Riemannian metric on the manifold of all smooth Riemannian metrics on a fixed closed, finite-dimensional manifold. The main body of the…

Differential Geometry · Mathematics 2009-04-02 Brian Clarke

Causal fermion systems and Riemannian fermion systems are proposed as a framework for describing non-smooth geometries. In particular, this framework provides a setting for spinors on singular spaces. The underlying topological structures…

Mathematical Physics · Physics 2019-05-06 Felix Finster , Niky Kamran

Following our approach to metric Lie algebras developed in math.DG/0312243 we propose a way of understanding pseudo-Riemannian symmetric spaces which are not semi-simple. We introduce cohomology sets (called quadratic cohomology) associated…

Differential Geometry · Mathematics 2007-05-23 Ines Kath , Martin Olbrich

This paper is a short summary of our recent work on the medians and means of probability measures in Riemannian manifolds. Firstly, the existence and uniqueness results of local medians are given. In order to compute medians in practical…

Differential Geometry · Mathematics 2011-11-16 Marc Arnaudon , Frédéric Barbaresco , Le Yang

This paper investigates the failure of certain metric measure spaces to be infinitesimally Hilbertian or quasi-Riemannian manifolds, by constructing examples arising from a manifold $M$ endowed with a Riemannian metric $g$ that is possibly…

Differential Geometry · Mathematics 2026-03-31 Vanessa Ryborz

For a class of Riemannian manifolds that include products of arbitrary compact manifolds with manifolds of nonpositive sectional curvature on the one hand, or with certain positive-curvature examples such as spheres of dimension at least 3…

Symplectic Geometry · Mathematics 2014-09-10 Michael Usher

We introduce slant Riemannian maps from Riemannian manifolds to almost Hermitian manifolds as a generalization of slant immersions, invariant Riemannian maps and anti-invariant Riemannian maps. We give examples, obtain characterizations and…

Differential Geometry · Mathematics 2012-06-18 Bayram Sahin

Let $N\subset M$ be a finite Jones' index inclusion of II$_1$ factors, and denote by $U_N\subset U_M$ their unitary groups. In this paper we study the homogeneous space $U_M/U_N$, which is a (infinite dimensional) differentiable manifold,…

Differential Geometry · Mathematics 2008-08-20 Esteban Andruchow , Gabriel Larotonda

We propose a solution to the problem of estimating a Riemannian metric associated with a given differentiable manifold. The metric learning problem is based on minimizing the relative volume of a given set of points. We derive the details…

Machine Learning · Computer Science 2012-12-12 Guy Lebanon

In the realm of robotics, numerous downstream robotics tasks leverage machine learning methods for processing, modeling, or synthesizing data. Often, this data comprises variables that inherently carry geometric constraints, such as the…

Robotics · Computer Science 2024-04-30 Noémie Jaquier , Leonel Rozo , Tamim Asfour

This paper proposes an original Riemmanian geometry for low-rank structured elliptical models, i.e., when samples are elliptically distributed with a covariance matrix that has a low-rank plus identity structure. The considered geometry is…

Differential Geometry · Mathematics 2020-01-07 Florent Bouchard , Arnaud Breloy , Guillaume Ginolhac , Alexandre Renaux , Frédéric Pascal

It is shown that a locally geometrical structure of arbitrarily curved Riemannian space is defined by a deformed group of its diffeomorphisms

Differential Geometry · Mathematics 2020-06-11 Serhiy E. Samokhvalov

We discuss some properties of the distance functions on Riemannian manifolds and we relate their behavior to the geometry of the manifolds. This leads to alternative proofs of some "classical" theorems connecting curvature and topology.

Differential Geometry · Mathematics 2026-02-20 Carlo Mantegazza , Francesca Oronzio

In this book chapter we study the Riemannian Geometry of the density registration problem: Given two densities (not necessarily probability densities) defined on a smooth finite dimensional manifold find a diffeomorphism which transforms…

Optimization and Control · Mathematics 2018-07-24 Martin Bauer , Sarang Joshi , Klas Modin

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…

A new geometrically exact micro-structured model is constructed using a generalisation of the notion of Riemann-Cartan manifolds and fibre bundle theory of rank 3. This model is based around the concept of two different length scales: a…

Differential Geometry · Mathematics 2024-04-05 Mewen Crespo , Guy Casale , Loïc Le Marrec

This paper aims to describe the behavior of diffeological differential forms under the operation of gluing of diffeological spaces along a smooth map. In the diffeological context, two ways of looking at diffeological forms are available,…

Differential Geometry · Mathematics 2025-03-26 Ekaterina Pervova

Riemannian geometry provides us with powerful tools to explore the latent space of generative models while preserving the underlying structure of the data. The latent space can be equipped it with a Riemannian metric, pulled back from the…

Machine Learning · Computer Science 2023-10-13 Alison Pouplin , David Eklund , Carl Henrik Ek , Søren Hauberg