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Cartan's method of moving frames is briefly recalled in the context of immersed curves in the homogeneous space of a Lie group $G$. The contact geometry of curves in low dimensional equi-affine geometry is then made explicit. This delivers…

Differential Geometry · Mathematics 2009-10-20 Peter J. Vassiliou

Most datasets encountered in computer vision and medical applications present symmetries that should be taken into account in classification tasks. A typical example is the symmetry by rotation and/or scaling in object detection. A common…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Ioana Ciuclea , Giorgio Longari , Alice Barbara Tumpach

The arithmetic of elliptic curves, namely polynomial addition and scalar multiplication, can be described in terms of global sections of line bundles on $E\times E$ and $E$, respectively, with respect to a given projective embedding of $E$…

Number Theory · Mathematics 2016-01-15 David Kohel

Motivated by applications in computational anatomy, we consider a second-order problem in the calculus of variations on object manifolds that are acted upon by Lie groups of smooth invertible transformations. This problem leads to solution…

Optimization and Control · Mathematics 2015-06-03 François Gay-Balmaz , Darryl D. Holm , David M. Meier , Tudor S. Ratiu , François-Xavier Vialard

We generalize the concept of sub-Riemannian geometry to infinite-dimensional manifolds modeled on convenient vector spaces. On a sub-Riemannian manifold $M$, the metric is defined only on a sub-bundle $\calH$ of the tangent bundle $TM$,…

Differential Geometry · Mathematics 2012-01-12 Erlend Grong , Irina Markina , Alexander Vasil'ev

Many phenomena are naturally characterized by measuring continuous transformations such as shape changes in medicine or articulated systems in robotics. Modeling the variability in such datasets requires performing statistics on Lie groups,…

Methodology · Statistics 2025-08-19 Johannes Schade , Christoph von Tycowicz , Martin Hanik

Representing graphs as sets of node embeddings in certain curved Riemannian manifolds has recently gained momentum in machine learning due to their desirable geometric inductive biases, e.g., hierarchical structures benefit from hyperbolic…

Machine Learning · Computer Science 2020-06-09 Calin Cruceru , Gary Bécigneul , Octavian-Eugen Ganea

We are interested in the geometry of the group $\mathcal{D}_q(M)$ of diffeomorphisms preserving a contact form $\theta$ on a manifold $M$. We define a Riemannian metric on $\mathcal{D}_q(M)$, compute the corresponding geodesic equation, and…

Differential Geometry · Mathematics 2013-02-21 David G. Ebin , Stephen C. Preston

The real symplectic Stiefel manifold is the manifold of symplectic bases of symplectic subspaces of a fixed dimension. It features in a large variety of applications in physics and engineering. In this work, we study this manifold with the…

Differential Geometry · Mathematics 2021-08-31 Thomas Bendokat , Ralf Zimmermann

The space of all non degenerate bilinear structures on a manifold $M$ carries a one parameter family of pseudo Riemannian metrics. We determine the geodesic equation, covariant derivative, curvature, and we solve the geodesic equation…

Differential Geometry · Mathematics 2016-09-06 Olga Gil-Medrano , Peter W. Michor , Martin Neuwirther

A class of elliptic-hyperbolic equations is placed in the context of a geometric variational theory, in which the change of type is viewed as a change in the character of an underlying metric. A fundamental example of a metric which changes…

Mathematical Physics · Physics 2009-11-13 Thomas H. Otway

This paper provides theoretical and computational developments in statistical shape analysis of shape graphs, and demonstrates them using analysis of complex data from retinal blood-vessel (RBV) networks. The shape graphs are represented by…

Methodology · Statistics 2022-11-29 Aditi Basu Bal , Xiaoyang Guo , Tom Needham , Anuj Srivastava

We address the problem of fitting parametric curves on the Grassmann manifold for the purpose of intrinsic parametric regression. As customary in the literature, we start from the energy minimization formulation of linear least-squares in…

Computer Vision and Pattern Recognition · Computer Science 2015-05-15 Yi Hong , Nikhil Singh , Roland Kwitt , Nuno Vasconcelos , Marc Niethammer

To any metric spaces there is an associated metric profile. The rectifiability of the metric profile gives a good notion of curvature of a sub-Riemannian space. We shall say that a curvature class is the rectifiability class of the metric…

Metric Geometry · Mathematics 2007-05-23 Marius Buliga

Modern machine learning increasingly leverages the insight that high-dimensional data often lie near low-dimensional, non-linear manifolds, an idea known as the manifold hypothesis. By explicitly modeling the geometric structure of data…

Machine Learning · Computer Science 2026-03-02 Willem Diepeveen , Deanna Needell

The classification of shapes is of great interest in diverse areas ranging from medical imaging to computer vision and beyond. While many statistical frameworks have been developed for the classification problem, most are strongly tied to…

Machine Learning · Statistics 2019-01-24 Min Ho Cho , Sebastian Kurtek , Steven N. MacEachern

Metrics on Lie groupoids and differentiable stacks have been introduced recently, extending the Riemannian geometry of manifolds and orbifolds to more general singular spaces. Here we continue that theory, studying stacky curves on…

Differential Geometry · Mathematics 2020-08-04 Matias del Hoyo , Mateus de Melo

We study completeness properties of Sobolev metrics on the space of immersed curves and on the shape space of unparametrized curves. We show that Sobolev metrics of order $n\geq 2$ are metrically complete on the space $\mathcal…

Differential Geometry · Mathematics 2015-04-09 Martins Bruveris

We analyze a variational time discretization of geodesic calculus on finite- and certain classes of infinite-dimensional Riemannian manifolds. We investigate the fundamental properties of discrete geodesics, the associated discrete…

Numerical Analysis · Mathematics 2013-03-25 Martin Rumpf , Benedikt Wirth

Biharmonic curves are a generalization of geodesics, with applications in elasticity theory and various branches of computer science. The paper proposes a first study of biharmonic curves in spaces with Finslerian geometry, covering the…

Differential Geometry · Mathematics 2013-07-23 Nicoleta Voicu