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Related papers: Tiling Hyperbolic Manifolds: Algorithms and Applic…

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The hyperbolic manifold is a smooth manifold of negative constant curvature. While the hyperbolic manifold is well-studied in the literature, it has gained interest in the machine learning and natural language processing communities lately…

Machine Learning · Computer Science 2019-03-19 Pratik Jawanpuria , Mayank Meghwanshi , Bamdev Mishra

We study the sup-norm and mean-square-norm problems for Eisenstein series on certain arithmetic hyperbolic orbifolds, producing sharp exponents for the modular surface and Picard 3-fold. The methods involve bounds for Epstein zeta…

Number Theory · Mathematics 2025-04-18 Dubi Kelmer , Alex Kontorovich , Christopher Lutsko

We demonstrate optimization of optical metasurfaces over $10^5$--$10^6$ degrees of freedom in two and three dimensions, 100--1000+ wavelengths ($\lambda$) in diameter, with 100+ parameters per $\lambda^2$. In particular, we show how…

Optics · Physics 2019-06-26 Zin Lin , Victor Liu , Raphaël Pestourie , Steven G. Johnson

Several articles deal with tilings with squares and dominoes on 2-dimensional boards, but only a few on boards in 3-dimensional space. We examine a tiling problem with colored cubes and bricks of $(2\times2\times n)$-board in three…

Combinatorics · Mathematics 2021-04-01 László Németh

Metric learning aims to learn a highly discriminative model encouraging the embeddings of similar classes to be close in the chosen metrics and pushed apart for dissimilar ones. The common recipe is to use an encoder to extract embeddings…

Computer Vision and Pattern Recognition · Computer Science 2022-03-23 Aleksandr Ermolov , Leyla Mirvakhabova , Valentin Khrulkov , Nicu Sebe , Ivan Oseledets

We provide a new approach for computing integrals over hypersurfaces in the level set framework. The method is based on the discretization (via simple Riemann sums) of the classical formulation used in the level set framework, with the…

Numerical Analysis · Mathematics 2017-03-08 Catherine Kublik , Richard Tsai

A recent preprint of S. Kojima and G. McShane [KM] observes a beautiful explicit connection between Teichm\"uller translation distance and hyperbolic volume. It relies on a key estimate which we supply here: using geometric inflexibility of…

Geometric Topology · Mathematics 2014-12-17 Jeffrey Brock , Kenneth Bromberg

We establish the geometric ergodicity of the preconditioned Hamiltonian Monte Carlo (HMC) algorithm defined on an infinite-dimensional Hilbert space, as developed in [Beskos et al., Stochastic Process. Appl., 2011]. This algorithm can be…

Statistics Theory · Mathematics 2020-03-19 Nathan E. Glatt-Holtz , Cecilia F. Mondaini

Under mild topological restrictions, we obtain new linear upper bounds for the dimension of the mod $p$ homology (for any prime $p$) of a finite-volume orientable hyperbolic $3$ manifold $M$ in terms of its volume. A surprising feature of…

Geometric Topology · Mathematics 2022-07-04 Rosemary K. Guzman , Peter B. Shalen

Learning graph representations via low-dimensional embeddings that preserve relevant network properties is an important class of problems in machine learning. We here present a novel method to embed directed acyclic graphs. Following prior…

Machine Learning · Computer Science 2018-06-08 Octavian-Eugen Ganea , Gary Bécigneul , Thomas Hofmann

We present a new numerical method for the isometric embedding of 2-geometries specified by their 2-metrics in three dimensional Euclidean space. Our approach is to directly solve the fundamental embedding equation supplemented by six…

General Relativity and Quantum Cosmology · Physics 2015-06-23 Wolfgang Tichy , Jonathan R. McDonald , Warner A. Miller

Liquid crystal elastomers and glasses can have significant shape change determined by their director patterns. Cones deformed from circular director patterns have non-trivial Gaussian curvature localised at tips, curved interfaces, and…

Soft Condensed Matter · Physics 2021-07-02 Fan Feng , John S. Biggins , Mark Warner

We describe an algorithm which has enabled us to give a complete list, without repetitions, of all closed oriented irreducible 3-manifolds of complexity up to 9. More interestingly, we have actually been able to give a "name" to each such…

Geometric Topology · Mathematics 2007-05-23 Bruno Martelli , Carlo Petronio

The purpose the present paper is to construct the hyperbolic trigonometry on Euclidean plane without refereing to hyperbolic plane. In this paper we show that the concept of hyperbolic angle and its functions forming the hyperbolic…

General Mathematics · Mathematics 2011-04-28 Robert M. Yamaleev

We derive basic differential geometric formulae for surfaces in hyperbolic space represented as envelopes of horospheres. The dual notion of parallel hypersurfaces is also studied. The representation is applied to prove existence and…

Differential Geometry · Mathematics 2025-07-01 Charles L. Epstein

We consider a volume maximization program to construct hyperbolic structures on triangulated 3-manifolds, for which previous progress has lead to consider angle assignments which do not correspond to a hyperbolic metric on each simplex. We…

Geometric Topology · Mathematics 2009-08-17 Feng Luo , Jean-Marc Schlenker

Plasmonic hyperbolic metasurfaces have emerged as an effective platform for manipulating the propagation of light. Here, confined modes on arrays of silver nanoridges that exhibit hyperbolic dispersion are used to demonstrate and model a…

We investigate the filling area conjecture, optimal systolic inequalities, and the related problem of the nonvanishing of certain linking numbers in 3-manifolds.

Differential Geometry · Mathematics 2016-09-07 Mikhail G. Katz , Christine Lescop

For X = R, C, or H it is well known that cusp cross-sections of finite volume X-hyperbolic (n+1)-orbifolds are flat n-orbifolds or almost flat orbifolds modelled on the (2n+1)-dimensional Heisenberg group N_{2n+1} or the (4n+3)-dimensional…

Geometric Topology · Mathematics 2014-10-01 D. B. McReynolds

Embedding the data in hyperbolic spaces can preserve complex relationships in very few dimensions, thus enabling compact models and improving efficiency of machine learning (ML) algorithms. The underlying idea is that hyperbolic…

Machine Learning · Computer Science 2025-01-14 Vladimir Jaćimović
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