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We study permutation-invariant embeddings of $d$-dimensional point sets, which are defined by sorting $D$ independent one-dimensional projections of the input. Such embeddings arise in graph deep learning where outputs should be invariant…

Machine Learning · Computer Science 2026-05-26 Nadav Dym , Matthias Wellershoff , Efstratios Tsoukanis , Daniel Levy , Radu Balan

This article surveys the use of configuration space integrals in the study of the topology of knot and link spaces. The main focus is the exposition of how these integrals produce finite type invariants of classical knots and links. More…

Geometric Topology · Mathematics 2013-10-29 Ismar Volic

Let $\mathbb{K}$ be an algebraically closed field of characteristic zero, and $V$ a hypersurface defined by an irreducible polynomial $f$ with coefficients in $\mathbb{K}$ . In this article we prove that an Embedded Deformation of $V$ which…

Algebraic Geometry · Mathematics 2018-06-26 Maximiliano Leyton-Álvarez

We identify the space of tangentially straightened long knots in R^m, for m greater than or equal to 4, as the double loops on the space of derived operad maps from the associative operad into a version of the little m-disk operad. This…

Algebraic Topology · Mathematics 2014-11-11 William Dwyer , Kathryn Hess

The homotopy fiber of the inclusion from the long embedding space to the long immersion space is known to be an iterated based loop space (if the codimension is greater than two). In this paper we deloop the homotopy fiber to obtain the…

Geometric Topology · Mathematics 2014-08-26 Keiichi Sakai

Arguably, geodesics are the most important geometric objects on a differentiable manifold. They describe candidates for shortest paths and are guaranteed to be unique shortest paths when the starting velocity stays within the so-called…

Numerical Analysis · Mathematics 2024-07-09 Jakob Stoye , Ralf Zimmermann

Nonlinear dimensionality reduction methods provide a valuable means to visualize and interpret high-dimensional data. However, many popular methods can fail dramatically, even on simple two-dimensional manifolds, due to problems such as…

Machine Learning · Statistics 2020-07-08 Daniel Ting , Michael I. Jordan

This paper is devoted to a systematic study and classification of invariant affine or metric connections on certain classes of naturally reductive spaces. For any non-symmetric, effective, strongly isotropy irreducible homogeneous…

Differential Geometry · Mathematics 2019-11-27 Ioannis Chrysikos , Christian O'Cadiz Gustad , Henrik Winther

It is shown that a covariant derivative on any d-dimensional manifold M can be mapped to a set of d operators acting on the space of functions on the principal Spin(d)-bundle over M. In other words, any d-dimensional manifold can be…

High Energy Physics - Theory · Physics 2009-11-11 Masanori Hanada , Hikaru Kawai , Yusuke Kimura

We present an intrinsic geometric classification of the supermanifold of maps from $\mathbb{R}^{0|2}$ to any smooth manifold $S$, avoiding auxiliary structures. The key isomorphism relates this space to the pullback of the decomposable…

Differential Geometry · Mathematics 2025-07-10 Zhiwei Yan

Take n>k>1 such that n-k is odd. In this paper we consider mapping a from (n-k+1)-dimensional closed ball into the space of (n \times k)--matrices such that its restriction to a sphere goes into the Stiefel manifold V_k(R^n). We construct a…

Algebraic Geometry · Mathematics 2015-09-15 Iwona Krzyżanowska , Aleksandra Nowel

For a topological space $X$ we study continuous maps $f : X\to \mathbb R^m$ such that images of every pairwise distinct $k$ points are affinely (linearly) independent. Such maps are called affinely (linearly) $k$-regular embeddings. We…

Algebraic Topology · Mathematics 2011-06-29 R. N. Karasev

Many machine learning problems involve regressing variables on a non-Euclidean manifold -- e.g. a discrete probability distribution, or the 6D pose of an object. One way to tackle these problems through gradient-based learning is to use a…

Computer Vision and Pattern Recognition · Computer Science 2021-10-14 Romain Brégier

In a previous paper [M.~Hanada, H.~Kawai and Y.~Kimura, Prog. Theor. Phys. 114 (2005), 1295] it is shown that a covariant derivative on any n-dimensional Riemannian manifold can be expressed in terms of a set of n matrices, and a new…

High Energy Physics - Theory · Physics 2008-11-26 Masanori Hanada

It is shown that in dimension at least three a local diffeomorphism of Euclidean n-space into itself is injective provided that the pull-back of every plane is a Riemannian submanifold which is conformal to a plane. Using a similar…

Differential Geometry · Mathematics 2020-03-02 Frederico Xavier

The defect $d(M,\rho)$ is an invariant of a compact oriented 3-manifold $M$ with a representation $\rho$ of the fundamental group. In this article we give a diagrammatic method for $d$ of knot exteriors by using knot diagrams.

Geometric Topology · Mathematics 2024-06-14 Tatsuro Shimizu

Given a compact manifold $M$ and a Riemannian manifold $N$ of bounded geometry, we consider the manifold ${\rm Imm} (M,N)$ of immersions from $M$ to $N$ and its subset ${\rm Imm}_\mu (M,N)$ of those immersions with the property that the…

Differential Geometry · Mathematics 2017-08-02 Martin Bauer , Peter Michor , Olaf Müller

Representing images and videos with Symmetric Positive Definite (SPD) matrices and considering the Riemannian geometry of the resulting space has proven beneficial for many recognition tasks. Unfortunately, computation on the Riemannian…

Computer Vision and Pattern Recognition · Computer Science 2014-11-18 Mehrtash T. Harandi , Mathieu Salzmann , Richard Hartley

We prove a theorem on equivariant maps implying the following two corollaries: (1) Let N and M be compact orientable n-manifolds with boundaries such that M\subset N, the inclusion M\to N induces an isomorphism in integral cohomology, both…

Geometric Topology · Mathematics 2012-07-06 D. Goncalves , A. Skopenkov

We consider the class of profinite diffeological spaces, that is, diffeological spaces which diffeologies are deduced by pull-back of diffeologies on finite-dimensional manifolds through a system of projection mappings. This class includes…

Differential Geometry · Mathematics 2025-10-29 Anahita Eslami-Rad , Jean-Pierre Magnot , Enrique G. Reyes
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