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In this paper, the concept of the metric matrix is introduced to establish a concise and unified formulation for the inner product in barycentric coordinates. Building on this framework, we explore the intrinsic algebraic identities of…

General Mathematics · Mathematics 2025-05-13 Xi Feng

The author proposes a new geometry in this book. The author named this new geometry Intercenter Geometry. Intercenter Geometry is different from traditional Euclidean geometry and analytic geometry (coordinate geometry). The idea of…

General Mathematics · Mathematics 2024-05-01 Daiyuan Zhang

In this paper, we generalize the notions of centroids and barycenters to the broad class of information-theoretic distortion measures called Bregman divergences. Bregman divergences are versatile, and unify quadratic geometric distances…

Computational Geometry · Computer Science 2007-11-22 Frank Nielsen , Richard Nock

The distance between the true and numerical solutions in some metric is considered as the discretization error magnitude. If error magnitude ranging is known, the triangle inequality enables the estimation of the vicinity of the approximate…

Computational Physics · Physics 2018-05-11 A. K. Alekseev , A. E. Bondarev , I. M. Navon

We determine barycentric coordinates of triangle centers in the elliptic plane. The main focus is put on centers that lie on lines whose euclidean limit (triangle excess --> 0) is the Euler line or the Brocard line. We also investigate…

Metric Geometry · Mathematics 2018-01-24 Manfred Evers

In this paper, we introduce an asymmetric metric on the space of marked Euclidean triangles, and we prove several properties of this metric, including two equivalent definitions of this metric, one of them comparing ratios of functions of…

Geometric Topology · Mathematics 2025-04-25 Ismail Saglam , Ken'Ichi Ohshika , Athanase Papadopoulos

Distances are pervasive in machine learning. They serve as similarity measures, loss functions, and learning targets; it is said that a good distance measure solves a task. When defining distances, the triangle inequality has proven to be a…

Machine Learning · Computer Science 2020-07-08 Silviu Pitis , Harris Chan , Kiarash Jamali , Jimmy Ba

Barycentric averaging is a principled way of summarizing populations of measures. Existing algorithms for estimating barycenters typically parametrize them as weighted sums of Diracs and optimize their weights and/or locations. However,…

Machine Learning · Statistics 2021-02-16 Samuel Cohen , Michael Arbel , Marc Peter Deisenroth

Given a triangulated surface, a polyhedral metric could be constructed by gluing Euclidean triangles edge-to-edge. We carefully describe the construction and prove that such a polyhedral metric is the only intrinsic metric on the glued…

Geometric Topology · Mathematics 2023-12-05 Tianqi Wu

Comparing representations across neural networks is challenging because representations admit symmetries, such as arbitrary reordering of units or rotations of activation space, that obscure underlying equivalence between models. We…

Machine Learning · Computer Science 2026-02-11 Shreya Saha , Zoe Wanying He , Meenakshi Khosla

Non-Euclidean triangle centers can be described using homogeneous coordinates that are proportional to the generalized sines of the directed distances of a given center from the edges of the reference triangle. Identical homogeneous…

Metric Geometry · Mathematics 2024-06-25 Robert A. Russell

We give three new proofs of the triangle inequality in Euclidean Geometry. There seems to be only one known proof at the moment. It is due to properties of triangles, but our proofs are due to circles or ellipses. We aim to prove the…

General Mathematics · Mathematics 2020-01-30 Norihiro Someyama , Mark Lyndon Adamas Borongan

A parameterization is described for quantifying translational motion of a point in three-dimensional Euclidean space. The parameterization is similar to well-known parameterizations such as spherical coordinates in that both position and…

Dynamical Systems · Mathematics 2020-11-24 Alexander T. Miller , Anil V. Rao

A configuration p in r-dimensional Euclidean space is a finite collection of labeled points p^1,p^2,...,p^n in R^r that affinely span R^r. Each configuration p defines a Euclidean distance matrix D_p = (d_ij) = (||p^i-p^j||^2), where ||.||…

Metric Geometry · Mathematics 2012-01-17 A. Y. Alfakih

This is a paper about triangle cubics and conics in classical geometry with elements of projective geometry. In recent years, N.J. Wildberger has actively dealt with this topic using an algebraic perspective. Triangle conics were also…

Metric Geometry · Mathematics 2021-01-12 Ruslan Skuratovskii , Veronika Strarodub

We study a function, which is a weighted sum of the squares of the distances of an arbitrary point to the sidelines of a triangle. The given weights, considered as barycentric coordinates, determine a point $M$. We prove that the function…

Metric Geometry · Mathematics 2016-04-19 Georgi Ganchev , Nikolai Nikolov

We investigate several topics of triangle geometry in the elliptic and in the extended hyperbolic plane, such as: centers based on orthogonality, centers related to circumcircles and incircles, radical centers and centers of similitude,…

Metric Geometry · Mathematics 2019-08-30 Manfred Evers

The problem of recovering the configuration of points from their partial pairwise distances, referred to as the Euclidean Distance Matrix Completion (EDMC) problem, arises in a broad range of applications, including sensor network…

Optimization and Control · Mathematics 2026-05-07 Chandler Smith , HanQin Cai , Abiy Tasissa

This paper considers the problem of measure estimation under the barycentric coding model (BCM), in which an unknown measure is assumed to belong to the set of Wasserstein-2 barycenters of a finite set of known measures. Estimating a…

Machine Learning · Statistics 2022-06-29 Matthew Werenski , Ruijie Jiang , Abiy Tasissa , Shuchin Aeron , James M. Murphy

We introduce a novel representation and optimization framework for discrete geodesics on triangle meshes that reduces artifacts of linear methods on uneven and coarse discretizations. Our method computes squared geodesic distances from…

Graphics · Computer Science 2026-03-04 Yue Ruan , Albert Chern , Tzu-Mao Li , Kartic Subr , Amir Vaxman
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