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A graph is called (generically) rigid in $\mathbb{R}^d$ if, for any choice of sufficiently generic edge lengths, it can be embedded in $\mathbb{R}^d$ in a finite number of distinct ways, modulo rigid transformations. Here we deal with the…

Computational Geometry · Computer Science 2017-01-26 Ioannis Z. Emiris , Ioannis Psarros

Standard Bayesian inference can build models that combine information from various sources, but this inference may not be reliable if components of a model are misspecified. Cut inference, as a particular type of modularized Bayesian…

Methodology · Statistics 2026-03-18 Yang Liu , Robert J. B. Goudie

One-dimensional cut-and-project point sets obtained from the square lattice in the plane are considered from a unifying point of view and in the perspective of aperiodic wavelet constructions. We successively examine their geometrical…

Mathematical Physics · Physics 2007-09-13 J. -P. Gazeau , Z. Masakova , E. Pelantova

This paper proposes a definition of recognizable transducers over monads and comonads, which bridges two important ongoing efforts in the current research on regularity. The first effort is the study of regular transductions, which extends…

Formal Languages and Automata Theory · Computer Science 2024-07-04 Rafał Stefański

We present examples of realcompact spaces with closed subsets that are C*-embedded but not C-embedded, including one where the closed set is a copy of the space of natural numbers.

General Topology · Mathematics 2023-08-28 Alan Dow , Jan van Mill , Klaas Pieter Hart , Hans Vermeer

In this paper, we prove that given a cut-and-project scheme $(G, H, \mathcal{L})$ and a compact window $W \subseteq H$, the natural projection gives a bijection between the Fourier transformable measures on $G \times H$ supported inside the…

Classical Analysis and ODEs · Mathematics 2021-11-24 Nicolae Strungaru

The theory of spin models intersects with condensed matter physics, complex systems, graph theory, combinatorial optimization, computational complexity and neural networks. Many ensuing applications rely on the fact that complicated spin…

Mathematical Physics · Physics 2024-08-02 Tobias Reinhart , Benjamin Engel , Gemma De les Coves

The space of embedded submanifolds plays an important role in applications such as computational anatomy and shape analysis. We can define two different classes on Riemannian metrics on this space: so-called outer metrics are metrics that…

Differential Geometry · Mathematics 2017-09-19 Martins Bruveris

We consider two disjoint sets of points. If at least one of the sets can be embedded into an Euclidean space, then we provide sufficient conditions for the two sets to be jointly embedded in one Euclidean space. In this joint Euclidean…

General Mathematics · Mathematics 2023-09-06 N. Alexia Raharinirina , Konstantin Fackeldey , Marcus Weber

We study intersections of projective convex sets in the sense of Steinitz. In a projective space, an intersection of a nonempty family of convex sets splits into multiple connected components each of which is a convex set. Hence, such an…

Metric Geometry · Mathematics 2010-05-12 Takahisa Toda

We consider the method of alternating projections for finding a point in the intersection of two closed sets, possibly nonconvex. Assuming only the standard transversality condition (or a weaker version thereof), we prove local linear…

Optimization and Control · Mathematics 2016-08-12 D. Drusvyatskiy , A. D. Ioffe , A. S. Lewis

In this paper, we investigate the extrapolation capabilities of implicit deep learning models in handling unobserved data, where traditional deep neural networks may falter. Implicit models, distinguished by their adaptability in layer…

Machine Learning · Computer Science 2024-07-22 Juliette Decugis , Alicia Y. Tsai , Max Emerling , Ashwin Ganesh , Laurent El Ghaoui

An open (resp., closed) subset A of a topological space (X, T ) is called C-open (resp., C-closed) set if cl(A) \ A (resp., A \ int(A)) is a countable set. This paper aims to present the concept of C-open and C-closed sets. We first…

General Topology · Mathematics 2023-05-08 M. H. Alqahtani

We firstly prove the completeness of the category of crossed modules in a modified category of interest. Afterwards, we define pullback crossed modules and pullback cat$^1$-objects that are both obtained by pullback diagrams with extra…

Category Theory · Mathematics 2019-03-13 Kadir Emir , Selim Çetin

The author has recently introduced the class of CNED sets in Euclidean space, generalizing the classical notion of NED sets, and shown that they are quasiconformally removable. A set $E$ is CNED if the conformal modulus of a curve family is…

Complex Variables · Mathematics 2025-02-17 Dimitrios Ntalampekos

Understanding the notion of a model is not always easy in logic courses. Hence, tools such as Euler diagrams are frequently applied as informal illustrations of set-theoretical models. We formally investigate Euler diagrams as an…

Computers and Society · Computer Science 2015-07-19 Ryo Takemura

A transduction provides us with a way of using the monadic second-order language of a structure to make statements about a derived structure. Any transduction induces a relation on the set of these structures. This article presents a…

Combinatorics · Mathematics 2024-01-24 Susan Jowett , Dillon Mayhew , Songbao Mo , Christopher Tuffley

For modules over a finite-dimensional algebra, there is a canonical one-to-one correspondence between the projective indecomposable modules and the simple modules. In this purely expository note, we take a straight-line path from the…

Rings and Algebras · Mathematics 2014-10-15 Tom Leinster

Pattern avoidance classes of permutations that cannot be expressed as unions of proper subclasses can be described as the set of subpermutations of a single bijection. In the case that this bijection is a permutation of the natural numbers…

Combinatorics · Mathematics 2007-05-23 M. D. Atkinson , M. M. Murphy , N. Ruskuc

Combining additive models and neural networks allows to broaden the scope of statistical regression and extend deep learning-based approaches by interpretable structured additive predictors at the same time. Existing attempts uniting the…

Machine Learning · Statistics 2022-07-12 David Rügamer , Chris Kolb , Nadja Klein