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Latent space geometry provides a rigorous and empirically valuable framework for interacting with the latent variables of deep generative models. This approach reinterprets Euclidean latent spaces as Riemannian through a pull-back metric,…

Machine Learning · Statistics 2024-08-15 Stas Syrota , Pablo Moreno-Muñoz , Søren Hauberg

We discuss the application of random projections to the fundamental problem of deciding whether a given point in a Euclidean space belongs to a given set. We show that, under a number of different assumptions, the feasibility and…

Optimization and Control · Mathematics 2015-11-19 Ky Vu , Pierre-Louis Poirion , Leo Liberti

Influence network of events is a view of the universe based on events that may be related to one another via influence. The network of events form a partially-ordered set which, when quantified consistently via a technique called chain…

Mathematical Physics · Physics 2024-10-29 Newshaw Bahreyni , Carlo Cafaro , Leonardo Rossetti

A coordinate system is a foundation for every quantitative science, engineering, and medicine. Classical physics and statistics are based on the Cartesian coordinate system. The classical probability and hypothesis testing theory can only…

Methodology · Statistics 2022-11-08 Kai Zhang , Shan Liu , Momiao Xiong

We study the problem of representing all distances between $n$ points in $\mathbb R^d$, with arbitrarily small distortion, using as few bits as possible. We give asymptotically tight bounds for this problem, for Euclidean metrics, for…

Computational Geometry · Computer Science 2021-10-08 Piotr Indyk , Tal Wagner

The Wigner spacing distribution has a long and illustrious history in nuclear physics and in the quantum mechanics of classically chaotic systems. In this paper, a novel connection between the Wigner distribution and 2D classical mechanics…

Chaotic Dynamics · Physics 2017-08-03 Jamal Sakhr

Euclidean geometry is among the earliest forms of mathematical thinking. While the geometric primitives underlying its constructions, such as perfect lines and circles, do not often occur in the natural world, humans rarely struggle to…

Computer Vision and Pattern Recognition · Computer Science 2022-12-01 Joy Hsu , Jiajun Wu , Noah D. Goodman

Every graph G can be embedded in a Euclidean space as a two-distance set. The Euclidean representation number of G is the smallest dimension in which G is representable by such an embedding. We consider spherical and J-spherical…

Metric Geometry · Mathematics 2019-06-26 Oleg R. Musin

Spatial networks are networks whose graph topology is constrained by their embedded spatial space. Understanding the coupled spatial-graph properties is crucial for extracting powerful representations from spatial networks. Therefore,…

Machine Learning · Computer Science 2024-01-11 Zheng Zhang , Sirui Li , Jingcheng Zhou , Junxiang Wang , Abhinav Angirekula , Allen Zhang , Liang Zhao

The enduring legacy of Euclidean geometry underpins classical machine learning, which, for decades, has been primarily developed for data lying in Euclidean space. Yet, modern machine learning increasingly encounters richly structured data…

This article is devoted to the study of classical and new results concerning equidistant sets, both from the topological and metric point of view. We start with a review of the most interesting known facts about these sets in the euclidean…

Metric Geometry · Mathematics 2012-01-13 Mario Ponce , Patricio Santibáñez

Recent literature has shown that symbolic data, such as text and graphs, is often better represented by points on a curved manifold, rather than in Euclidean space. However, geometrical operations on manifolds are generally more complicated…

Machine Learning · Computer Science 2019-02-06 Max Aalto , Nakul Verma

By recasting metrical geometry in a purely algebraic setting, both Euclidean and non-Euclidean geometries can be studied over a general field with an arbitrary quadratic form. Both an affine and a projective version of this new theory are…

Metric Geometry · Mathematics 2007-05-23 Norman J. Wildberger

As one type of incidence theory, the geometry of pentagram map seems quite classical at first. However, this is an excellent example of such a classical idea developed into a marvellous insight by some modern approach. We introduce an…

Differential Geometry · Mathematics 2023-08-09 Yusaku Mori

One interpretation of how the classical world emerges from an underlying quantum reality involves the build-up of certain robust entanglements between particles due to scattering events [Science Vol.301 p.1081]. This is an appealing view…

Quantum Physics · Physics 2013-04-26 P. A. Knott , J. Sindt , J. A. Dunningham

Detecting poorly textured objects and estimating their 3D pose reliably is still a very challenging problem. We introduce a simple but powerful approach to computing descriptors for object views that efficiently capture both the object…

Computer Vision and Pattern Recognition · Computer Science 2017-11-15 Paul Wohlhart , Vincent Lepetit

In this paper we give a combinatorial characterization of projections of geodesics in Euclidean buildings to Weyl chambers. We apply these results to the representation theory of complex semisimple Lie groups and to spherical Hecke rings…

Representation Theory · Mathematics 2008-07-01 Michael Kapovich , John J. Millson

We generalize classical large deviations theorems to the setting of complete Riemannian manifolds. We prove the analogue of Mogulskii's theorem for geodesic random walks via a general approach using visocity solutions for Hamilton-Jacobi…

Probability · Mathematics 2020-03-31 Richard C. Kraaij , Frank Redig , Rik Versendaal

Constructive-deductive method for plane Euclidean geometry is proposed and formalized within Coq Proof Assistant. This method includes both postulates that describe elementary constructions by idealized geometric tools (pencil, straightedge…

Logic · Mathematics 2019-03-14 Evgeny V. Ivashkevich

The class of Schoenberg transformations, embedding Euclidean distances into higher dimensional Euclidean spaces, is presented, and derived from theorems on positive definite and conditionally negative definite matrices. Original results on…

Machine Learning · Statistics 2015-03-13 François Bavaud