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The enormous amount of data to be represented using large graphs exceeds in some cases the resources of a conventional computer. Edges in particular can take up a considerable amount of memory as compared to the number of nodes. However,…

Artificial Intelligence · Computer Science 2023-12-18 Faisal N. Abu-Khzam , Rana H. Mouawi , Amer Hajj Ahmad , Sergio Thoumi

In this paper, we develop the theory of Sobolev spaces on locally finite graphs, including completeness, reflexivity, separability, and Sobolev inequalities. Since there is no exact concept of dimension on graphs, classical methods that…

Analysis of PDEs · Mathematics 2023-06-28 Mengqiu Shao , Yunyan Yang , Liang Zhao

We consider the quasihyperbolic metric, and its generalizations in both the $n$-dimensional Euclidean space $R^n$, and in Banach spaces. Historical background, applications, and our recent work on convexity properties of these metrics are…

Complex Variables · Mathematics 2015-03-19 Riku Klén , Antti Rasila , Jarno Talponen

In this paper, we study planar drawings of maximal outerplanar graphs with the objective of achieving small height. A recent paper gave an algorithm for such drawings that is within a factor of 4 of the optimum height. In this paper, we…

Data Structures and Algorithms · Computer Science 2017-02-07 Therese Biedl , Philippe Demontigny

Non-Euclidean foundation models increasingly place representations in curved spaces such as hyperbolic geometry. We show that this geometry creates a boundary-driven asymmetry that backdoor triggers can exploit. Near the boundary, small…

Machine Learning · Computer Science 2025-10-09 Ali Baheri

A random geometric graph, $G(n,r)$, is formed by choosing $n$ points independently and uniformly at random in a unit square; two points are connected by a straight-line edge if they are at Euclidean distance at most $r$. For a given…

Discrete Mathematics · Computer Science 2018-10-01 Ahmad Biniaz , Evangelos Kranakis , Anil Maheshwari , Michiel Smid

Hyperbolicity is a property of a graph that may be viewed as being a "soft" version of a tree, and recent empirical and theoretical work has suggested that many graphs arising in Internet and related data applications have hyperbolic…

Social and Information Networks · Computer Science 2013-09-17 Wei Chen , Wenjie Fang , Guangda Hu , Michael W. Mahoney

The unit distance embeddability of a graph, like planarity, involves a mix of constraints that are combinatorial and geometric. We construct a unit distance embedding for $H-e$ in the hope that it will lead to an embedding for $H$. We then…

Combinatorics · Mathematics 2007-11-08 Mitchell A. Harris

In this paper we establish the short-time existence and uniqueness theorem for hyperbolic geometric flow, and prove the nonlinear stability of hyperbolic geometric flow defined on the Euclidean space with dimension larger than 4. Wave…

Differential Geometry · Mathematics 2007-05-23 Wen-Rong Dai , De-Xing Kong , Kefeng Liu

In this note we develop a tool box of non-Euclidean plane geometry methods that yield a constructive way to define in terms of closed geodesics the Goldman bracket on deformation classes of closed, directed curves. We use this construction…

Geometric Topology · Mathematics 2023-08-07 Moira Chas , Arpan Kabiraj

We show that for any closed surface of genus greater than one and for any finite weighted graph filling the surface, there exists a hyperbolic metric which realizes the least Dirichlet energy harmonic embedding of the graph among a fixed…

Differential Geometry · Mathematics 2020-07-27 Toru Kajigaya , Ryokichi Tanaka

Unit disk graphs are intersection graphs of circles of unit radius in the plane. We present simple and provably good heuristics for a number of classical NP-hard optimization problems on unit disk graphs. The problems considered include…

Combinatorics · Mathematics 2016-09-06 Madhav V. Marathe , H. Breu , Harry B. Hunt , S. S. Ravi , Daniel J. Rosenkrantz

Optimal transportation distances are valuable for comparing and analyzing probability distributions, but larger-scale computational techniques for the theoretically favorable quadratic case are limited to smooth domains or regularized…

Other Computer Science · Computer Science 2016-03-23 Justin Solomon , Raif Rustamov , Leonidas Guibas , Adrian Butscher

Diffusion generative models (DMs) have achieved promising results in image and graph generation. However, real-world graphs, such as social networks, molecular graphs, and traffic graphs, generally share non-Euclidean topologies and hidden…

Machine Learning · Computer Science 2024-01-04 Lingfeng Wen , Xuan Tang , Mingjie Ouyang , Xiangxiang Shen , Jian Yang , Daxin Zhu , Mingsong Chen , Xian Wei

Neural embeddings have been used with great success in Natural Language Processing (NLP). They provide compact representations that encapsulate word similarity and attain state-of-the-art performance in a range of linguistic tasks. The…

Machine Learning · Statistics 2018-09-20 Benjamin Paul Chamberlain , James Clough , Marc Peter Deisenroth

The fine curve graph of a surface is a graph whose vertices are essential simple closed curves and whose edges connect disjoint curves. Following a rich history of hyperbolicity of various graphs associated to surfaces, the fine curve graph…

Geometric Topology · Mathematics 2026-04-29 Ryan Dickmann , Roberta Shapiro

We introduce decorated piecewise hyperbolic and spherical surfaces and discuss their discrete conformal equivalence. A decoration is a choice of circle about each vertex of the surface. Our decorated surfaces are closely related to…

Geometric Topology · Mathematics 2023-10-27 Alexander I. Bobenko , Carl O. R. Lutz

When considering geometry, one might think of working with lines and circles on a flat plane as in Euclidean geometry. However, doing geometry in other spaces is possible, as the existence of spherical and hyperbolic geometry demonstrates.…

General Mathematics · Mathematics 2024-04-01 Michael Perez Palapa , Kai Williams

Two-sample tests utilizing a similarity graph on observations are useful for high-dimensional and non-Euclidean data due to their flexibility and good performance under a wide range of alternatives. Existing works mainly focused on sparse…

Statistics Theory · Mathematics 2023-11-14 Yejiong Zhu , Hao Chen

Foundation models pre-trained on massive datasets, including large language models (LLMs), vision-language models (VLMs), and large multimodal models, have demonstrated remarkable success in diverse downstream tasks. However, recent studies…

Machine Learning · Computer Science 2025-07-25 Neil He , Hiren Madhu , Ngoc Bui , Menglin Yang , Rex Ying
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