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In this paper we construct spanning trees in hyperbolic graphs that represent their hyperbolic compactification in a good way: so that the tree has a bounded number of distinct rays to each boundary point. The bound depends only on the…

Combinatorics · Mathematics 2013-01-31 Matthias Hamann

For $p\in[1,\infty]$, the $\ell^p$ directed spanning forest (DSF) of dimension $d\geq 2$ is an oriented random geometric graph whose vertex set is given by a homogeneous Poisson point process $\mathcal N$ on $\mathbb R^d$ and whose edges…

Probability · Mathematics 2025-09-16 Tom Garcia-Sanchez

Geometric representation learning has recently shown great promise in several machine learning settings, ranging from relational learning to language processing and generative models. In this work, we consider the problem of performing…

Machine Learning · Statistics 2020-05-29 Gian Maria Marconi , Lorenzo Rosasco , Carlo Ciliberto

A general formulation is presented for continuum scaling limits of stochastic spanning trees. A spanning tree is expressed in this limit through a consistent collection of subtrees, which includes a tree for every finite set of endpoints in…

Probability · Mathematics 2012-06-19 Michael Aizenman , Almut Burchard , Charles M. Newman , David B. Wilson

A $(1+\varepsilon)$-stretch tree cover of an edge-weighted $n$-vertex graph $G$ is a collection of trees, where every pair of vertices has a $(1+\varepsilon)$-stretch path in one of the trees. The celebrated Dumbbell Theorem by Arya et. al.…

Data Structures and Algorithms · Computer Science 2025-03-31 Hsien-Chih Chang , Jonathan Conroy , Hung Le , Shay Solomon , Cuong Than

We study the structure of infinite geodesics in the Planar Stochastic Hyperbolic Triangulations $\mathbb{T}_{\lambda}$, which are the hyperbolic analogs of the UIPT. We prove that these geodesics form a supercritical Galton--Watson tree…

Probability · Mathematics 2019-04-30 Thomas Budzinski

Hyperbolic spaces provide a natural geometry for representing hierarchical and tree-structured data due to their exponential volume growth. To leverage these benefits, neural networks require intrinsic and efficient components that operate…

Machine Learning · Computer Science 2026-02-26 Ziheng Chen , Bernhard Schölkopf , Nicu Sebe

New examples of harmonic unit vector fields on hyperbolic 3-space are constructed by exploiting the reduction of symmetry arising from the foliation by horospheres. This is compared and contrasted with the analogous construction in…

Differential Geometry · Mathematics 2007-12-31 C. M. Wood

We show that the law of the three-dimensional uniform spanning tree (UST) is tight under rescaling in a space whose elements are measured, rooted real trees, continuously embedded into Euclidean space. We also establish that the relevant…

Probability · Mathematics 2021-12-30 Omer Angel , David A. Croydon , Sarai Hernandez-Torres , Daisuke Shiraishi

We introduce a concept of tree-graded metric space and we use it to show quasi-isometry invariance of certain classes of relatively hyperbolic groups, to obtain a characterization of relatively hyperbolic groups in terms of their asymptotic…

Geometric Topology · Mathematics 2009-09-29 Cornelia Drutu , Mark Sapir

The need to understand the structure of hierarchical or high-dimensional data is present in a variety of fields. Hyperbolic spaces have proven to be an important tool for embedding computations and analysis tasks as their non-linear nature…

Human-Computer Interaction · Computer Science 2024-01-26 Martin Skrodzki , Hunter van Geffen , Nicolas F. Chaves-de-Plaza , Thomas Höllt , Elmar Eisemann , Klaus Hildebrandt

A $(1+\varepsilon)\textit{-stretch tree cover}$ of a metric space is a collection of trees, where every pair of points has a $(1+\varepsilon)$-stretch path in one of the trees. The celebrated $\textit{Dumbbell Theorem}$ [Arya et~al.…

Computational Geometry · Computer Science 2024-03-27 Hsien-Chih Chang , Jonathan Conroy , Hung Le , Lazar Milenkovic , Shay Solomon , Cuong Than

The Binary Space Partitioning~(BSP)-Tree process is proposed to produce flexible 2-D partition structures which are originally used as a Bayesian nonparametric prior for relational modelling. It can hardly be applied to other learning tasks…

Machine Learning · Statistics 2019-03-25 Xuhui Fan , Bin Li , Scott Anthony Sisson

We present some explicit constructions of universal R-trees with applications to the asymptotic geometry of hyperbolic spaces. In particular, we show that any asymptotic cone of a complete simply connected manifold of negative curvature is…

Differential Geometry · Mathematics 2007-05-23 Anna Dyubina , Iosif Polterovich

We survey the distributional properties of progressively dilating sets under projection by covering maps, focusing on manifolds of constant sectional curvature. In the Euclidean case, we review previously known results and formulate some…

Dynamical Systems · Mathematics 2024-09-10 Emilio Corso

Hyperbolic spaces, which have the capacity to embed tree structures without distortion owing to their exponential volume growth, have recently been applied to machine learning to better capture the hierarchical nature of data. In this…

Machine Learning · Computer Science 2021-03-18 Ryohei Shimizu , Yusuke Mukuta , Tatsuya Harada

For a two-dimensional lattice $\Lambda$ with $n$ vertices, the number of spanning trees $N_{ST}(\Lambda)$ grows asymptotically as $\exp(n z_\Lambda)$ in the thermodynamic limit. We present exact integral expression and numerical value for…

Statistical Mechanics · Physics 2013-12-12 Shu-Chiuan Chang

The first main result of this paper is that the law of the (rescaled) two-dimensional uniform spanning tree is tight in a space whose elements are measured, rooted real trees continuously embedded into Euclidean space. Various properties of…

Probability · Mathematics 2017-07-04 M. T. Barlow , D. A. Croydon , T. Kumagai

We define branched bending deformations as deformations supported on a piecewise totally geodesic complex of $(n-1)$-dimensional faces meeting along $(n-2)$-dimensional branching loci. These are a generalization of bending deformations, as…

Geometric Topology · Mathematics 2026-04-27 Casandra D. Monroe

Multidimensional scaling (MDS) is a widely used approach to representing high-dimensional, dependent data. MDS works by assigning each observation a location on a low-dimensional geometric manifold, with distance on the manifold…

Methodology · Statistics 2023-08-16 Bolun Liu , Shane Lubold , Adrian E. Raftery , Tyler H. McCormick