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Related papers: Equiangular tight frames with centroidal symmetry

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Spherical equivariant graph neural networks (EGNNs) provide a principled framework for learning on three-dimensional molecular and biomolecular systems, where predictions must respect the rotational symmetries inherent in physics. These…

Machine Learning · Computer Science 2025-12-17 Sophia Tang

This paper investigates the existence and properties of spherical $5$-designs of minimal type. We focus on two cases: tight spherical $5$-designs and antipodal spherical $4$-distance $5$-designs. We prove that a tight spherical $5$-design…

Combinatorics · Mathematics 2025-08-27 Sho Suda , Zili Xu , Wei-Hsuan Yu

Core-periphery structure is an emerging property of a wide range of complex systems and indicate the presence of group of actors in the system with an higher number of connections among them and a lower number of connections with a sparsely…

Social and Information Networks · Computer Science 2020-06-24 Paolo Barucca

Pointed pseudo-triangulations are planar minimally rigid graphs embedded in the plane with pointed vertices (adjacent to an angle larger than 180 degrees. In this paper we prove that the opposite statement is also true, namely that planar…

The relation between equiangular sets of lines in the real space and distance-regular double covers of the complete graph is well known and studied since the work of Seidel and others in the 70's. The main topic of this paper is to continue…

Combinatorics · Mathematics 2018-05-23 Gabriel Coutinho , Chris Godsil , Mirhamed Shirazi , Harmony Zhan

We introduce probabilistic frames to study finite frames whose elements are chosen at random. While finite tight frames generalize orthonormal bases by allowing redundancy, independent, uniformly distributed points on the sphere…

Probability · Mathematics 2011-08-11 Martin Ehler

A classical branch of graph algorithms is graph transversals, where one seeks a minimum-weight subset of nodes in a node-weighted graph $G$ which intersects all copies of subgraphs~$F$ from a fixed family $\mathcal F$. Many such graph…

Data Structures and Algorithms · Computer Science 2021-08-03 Alexander Göke , Jochen Koenemann , Matthias Mnich , Hao Sun

A framework is a graph and a map from its vertices to R^d. A framework is called universally rigid if there is no other framework with the same graph and edge lengths in R^d' for any d'. A framework attachment is a framework constructed by…

Metric Geometry · Mathematics 2010-11-23 Kiril Ratmanski

Let $RG$ be the group ring of a finite group $G$ over a commutative ring $R$ with $1$. An element $x$ in $RG$ is said to be skew-symmetric with respect to an involution $\sigma$ of $RG$ if $\sigma(x)=-x.$ A structure theorem for the…

Rings and Algebras · Mathematics 2020-03-24 Dishari Chaudhuri

In this paper, we study sequences of perfect t-embeddings of a uniformly weighted family of graphs we call generalized tower graphs. We show that the embeddings of these graphs satisfy certain technical assumptions, in particular, the…

Mathematical Physics · Physics 2025-09-24 David Keating , Hieu Trung Vu

Random $s$-intersection graphs have recently received considerable attention in a wide range of application areas. In such a graph, each vertex is equipped with a set of items in some random manner, and any two vertices establish an…

Physics and Society · Physics 2015-02-03 Jun Zhao , Osman Yağan , Virgil Gligor

Edge-girth-regular graphs (abbreviated as \emph{egr} graphs) are regular graphs in which every edge is contained in the same number of shortest cycles. We prove that there is no $3$-regular \emph{egr} graph with girth $7$ such that every…

Combinatorics · Mathematics 2024-04-01 Leen Droogendijk

Symmetries are ubiquitous in real networks and often characterize network features and functions. Here we present a generalization of network symmetry called \emph{latent symmetry}, which is an extension of the standard notion of symmetry.…

Physics and Society · Physics 2018-10-17 Dallas Smith , Benjamin Webb

Group equivariant convolutional networks (GCNNs) endow classical convolutional networks with additional symmetry priors, which can lead to a considerably improved performance. Recent advances in the theoretical description of GCNNs revealed…

Machine Learning · Computer Science 2021-01-22 Leon Lang , Maurice Weiler

The topological Hochschild homology of a ring (or ring spectrum) $R$ is an $S^1$-spectrum, and the fixed points of THH($R$) for subgroups $C_n\subset S^1$ have been widely studied due to their use in algebraic K-theory computations.…

Algebraic Topology · Mathematics 2025-04-17 Anna Marie Bohmann , Teena Gerhardt , Cameron Krulewski , Sarah Petersen , Lucy Yang

Finite frames, or spanning sets for finite-dimensional Hilbert spaces, are a ubiquitous tool in signal processing. There has been much recent work on understanding the global structure of collections of finite frames with prescribed…

Functional Analysis · Mathematics 2023-09-14 Tom Needham , Clayton Shonkwiler

The symmetric edge polytope (SEP) of a (finite, undirected) graph is a centrally symmetric lattice polytope whose vertices are defined by the edges of the graph. SEPs have been studied extensively in the past twenty years. Recently,…

Combinatorics · Mathematics 2026-05-19 Robert Davis , Akihiro Higashitani , Hidefumi Ohsugi

We introduce a new class of frames with strong symmetry properties called geometrically uniform frames (GU), that are defined over an abelian group of unitary matrices and are generated by a single generating vector. The notion of GU frames…

Functional Analysis · Mathematics 2007-07-16 Yonina C. Eldar , H. Bolcskei

We give an algorithmic and lower-bound framework that facilitates the construction of subexponential algorithms and matching conditional complexity bounds. It can be applied to intersection graphs of similarly-sized fat objects, yielding…

Computational Geometry · Computer Science 2020-12-18 Mark de Berg , Hans L. Bodlaender , Sándor Kisfaludi-Bak , Dániel Marx , Tom C. van der Zanden

GBP and EP are two successful algorithms for approximate probabilistic inference, which are based on different approximation strategies. An open problem in both algorithms has been how to choose an appropriate approximation structure. We…

Artificial Intelligence · Computer Science 2012-07-09 Max Welling , Thomas P. Minka , Yee Whye Teh