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The purpose of this paper is to describe and elaborate the philosophical ideas behind hyperstructures and structure formation in general and emphasize the key ideas of the Hyperstructure Program.

General Mathematics · Mathematics 2019-03-21 Nils A. Baas

Modeling the inherent hierarchical structure of 3D objects and 3D scenes is highly desirable, as it enables a more holistic understanding of environments for autonomous agents. Accomplishing this with implicit representations, such as…

Computer Vision and Pattern Recognition · Computer Science 2025-10-27 Lisa Weijler , Sebastian Koch , Fabio Poiesi , Timo Ropinski , Pedro Hermosilla

We describe our initial explorations in simulating non-euclidean geometries in virtual reality. Our simulations of three-dimensional hyperbolic space are available at http://h3.hypernom.com.

History and Overview · Mathematics 2017-02-15 Vi Hart , Andrea Hawksley , Elisabetta A. Matsumoto , Henry Segerman

This is the first in a series of papers showing that Haken manifolds have hyperbolic structures; this first was published, the second two have existed only in preprint form, and later preprints were never completed. This eprint is only an…

Geometric Topology · Mathematics 2007-05-23 William P. Thurston

In this paper, we study diagonal hyperbolic systems in one space dimension. Based on a new gradient entropy estimate, we prove the global existence of a continuous solution, for large and non-decreasing initial data. We remark that these…

Mathematical Physics · Physics 2009-04-14 Ahmad El Hajj , Régis Monneau

Deep representation learning is a ubiquitous part of modern computer vision. While Euclidean space has been the de facto standard manifold for learning visual representations, hyperbolic space has recently gained rapid traction for learning…

Computer Vision and Pattern Recognition · Computer Science 2023-05-12 Pascal Mettes , Mina Ghadimi Atigh , Martin Keller-Ressel , Jeffrey Gu , Serena Yeung

Deep Learning is mostly responsible for the surge of interest in Artificial Intelligence in the last decade. So far, deep learning researchers have been particularly successful in the domain of image processing, where Convolutional Neural…

Machine Learning · Computer Science 2023-08-31 Andrii Skliar , Maurice Weiler

In contrast to the classical twistor spaces whose fibres are 2-spheres, we introduce twistor spaces over manifolds with almost quaternionic structures of the second kind in the sense of P. Libermann whose fibres are hyperbolic planes. We…

Differential Geometry · Mathematics 2007-05-23 D. E. Blair , J. Davidov , O. Mushkarov

How can we represent hierarchical information present in large type inventories for entity typing? We study the ability of hyperbolic embeddings to capture hierarchical relations between mentions in context and their target types in a…

Computation and Language · Computer Science 2019-06-07 Federico López , Benjamin Heinzerling , Michael Strube

The purpose of this work is to review, clarify, and critically analyse modern mathematical cosmology. The emphasis is upon mathematical objects and structures, rather than numerical computations. This paper concentrates on general…

General Relativity and Quantum Cosmology · Physics 2007-05-23 Gordon McCabe

In this work we investigate the following isoperimetric problem: to find the regions of prescribed volume with minimal boundary area between two parallel horospheres in hyperbolic 3-space (the area of the part of the boundary contained in…

Differential Geometry · Mathematics 2008-11-10 Rosa Chaves , Renato Pedrosa , Marcio Silva

General expository paper concerning topics in Hilbert spaces, spectral theory, and harmonic analysis. The preliminary section includes basic Banach algebra and Hilbert space theory with a digression on Riesz bases. The second and third…

Functional Analysis · Mathematics 2019-10-01 Sawyer Jack Robertson

In this article we explore the relationship between the systole and the diameter of closed hyperbolic orientable surfaces. We show that they satisfy a certain inequality, which can be used to deduce that their ratio has a (genus dependent)…

Geometric Topology · Mathematics 2023-04-03 Florent Balacheff , Vincent Despré , Hugo Parlier

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

This survey focuses on the computational complexity of some of the fundamental decision problems in 3-manifold theory. The article discusses the wide variety of tools that are used to tackle these problems, including normal and almost…

Geometric Topology · Mathematics 2020-02-07 Marc Lackenby

A sketch of the chapter appearing under the same heading in the book ``New Optimization Algorithms in Physics'' (A.K. Hartmann and H. Rieger, Eds.) is given. After a general introduction to spin glasses, important aspects of heuristic…

Disordered Systems and Neural Networks · Physics 2007-05-23 Olivier C. Martin

Hypersemitoric systems are 2-degree-of-freedom integrable systems on 4-dimensional manifolds that have an underlying $S^1$-symmetry and no degenerate singularities apart from maybe a finite number of families of so-called parabolic…

Dynamical Systems · Mathematics 2023-09-06 Yannick Gullentops , Sonja Hohloch

An encyclopedia article on mathematical aspects of quantum field theory in curved spacetime. Section titles are: Introduction and preliminaries; Construction of *-algebra for a real linear scalar field on globally hyperbolic spacetimes and…

General Relativity and Quantum Cosmology · Physics 2007-08-09 Bernard S. Kay

This article is a first step in the study of equations in periodic groups. As an application, we study the structure of periodic quotients of hyperbolic groups. We investigate for instance the Hopf and co-Hopf properties, the isomorphism…

Group Theory · Mathematics 2024-08-20 Rémi Coulon , Zlil Sela

Hierarchical models are increasingly used in many applications. Along with this increased use comes a desire to investigate whether the model is compatible with the observed data. Bayesian methods are well suited to eliminate the many…

Methodology · Statistics 2008-02-08 M. J. Bayarri , M. E. Castellanos