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We give upper and lower bounds for the Hausdorff dimensions for a class of graph-directed measures when its underlying directed graph is the infinite N-ary tree. These measures are different from graph-directed self-similar measures driven…

Classical Analysis and ODEs · Mathematics 2020-04-28 Kazuki Okamura

Low-pass graph filters are fundamental for signal processing on graphs and other non-Euclidean domains. However, the computation of such filters for parametric graph families can be prohibitively expensive as computation of the…

Machine Learning · Computer Science 2025-10-28 Anton Savostianov , Michael T. Schaub , Benjamin Stamm

Gaussian processes (GPs) are broadly used as surrogate models for expensive computer simulators of complex phenomena. However, a key bottleneck is that its training data are generated from this expensive simulator and thus can be highly…

Methodology · Statistics 2025-07-15 Liang Ding , Simon Mak , C. F. Jeff Wu

The metric dimension of a graph is the smallest number of nodes required to identify all other nodes based on shortest path distances uniquely. Applications of metric dimension include discovering the source of a spread in a network,…

Combinatorics · Mathematics 2021-04-16 Richard C. Tillquist , Rafael M. Frongillo , Manuel E. Lladser

A drawing in the plane ($\mathbb{R}^2$) of a graph $G=(V,E)$ equipped with a function $\gamma: V \rightarrow \mathbb{N}$ is \emph{$x$-bounded} if (i) $x(u) <x(v)$ whenever $\gamma(u)<\gamma(v)$ and (ii) $\gamma(u)\leq\gamma(w)\leq…

Computational Geometry · Computer Science 2016-10-25 Radoslav Fulek

In manifold learning, algorithms based on graph Laplacians constructed from data have received considerable attention both in practical applications and theoretical analysis. In particular, the convergence of graph Laplacians obtained from…

Machine Learning · Computer Science 2011-05-23 Xueyuan Zhou , Mikhail Belkin

The aim of this paper is to give an upper bound for the intrinsic diameter of a surface with boundary immersed in a conformally flat three dimensional Riemannian manifold in terms of the integral of the mean curvature and of the length of…

Differential Geometry · Mathematics 2023-03-20 Marco Flaim , Christian Scharrer

We investigate whether there is a relationship between the discrete Bakry-\'{E}mery curvature of a graph and the smooth curvature of an ambient surface into which the graph is embedded geodesically. As we used weighted graphs as test…

Combinatorics · Mathematics 2023-11-10 Gökçe Çakmak , Ali Deniz , Şahin Koçak , Murat Limoncu

We develop a functional model for operators arising in the study of boundary-value problems of materials science and mathematical physics. We then provide explicit formulae for the resolvents of the associated extensions of symmetric…

Analysis of PDEs · Mathematics 2022-05-10 Kirill D. Cherednichenko , Alexander V. Kiselev , Luis O. Silva

We define a special case of tree decompositions for planar graphs that respect a given embedding of the graph. We study the analogous width of the resulting decomposition we call the embedded-width of a plane graph. We show both upper…

Discrete Mathematics · Computer Science 2017-03-23 Glencora Borradaile , Jeff Erickson , Hung Le , Robbie Weber

In this article, the enumeration of partial chord diagrams is discussed via matrix model techniques. In addition to the basic data such as the number of backbones and chords, we also consider the Euler characteristic, the backbone spectrum,…

By our definition, "restricted Dirichlet-to-Neumann map" (DN) means that the Dirichlet and Neumann boundary data for a Coefficient Inverse Problem (CIP) are generated by a point source running along an interval of a straight line. On the…

Numerical Analysis · Mathematics 2017-08-08 Michael V. Klibanov

Existing approaches for classifying dynamic graphs either lift graph kernels to the temporal domain, or use graph neural networks (GNNs). However, current baselines have scalability issues, cannot handle a changing node set, or do not take…

Machine Learning · Computer Science 2023-10-24 Franz Srambical , Bastian Rieck

Spectral Graph Convolutional Networks (spectral GCNNs), a powerful tool for analyzing and processing graph data, typically apply frequency filtering via Fourier transform to obtain representations with selective information. Although…

Machine Learning · Computer Science 2023-05-04 Lequan Lin , Junbin Gao

As implied by the plethora of literature on graph rewiring, the choice of computational graph employed by a neural network can make a significant impact on its downstream performance. Certain effects related to the computational graph, such…

Machine Learning · Computer Science 2025-06-03 Alex Vitvitskyi , João G. M. Araújo , Marc Lackenby , Petar Veličković

We study a twisted version of Fraser, Lam, and Le's higher boundary measurement map, using face weights instead of edge weights, thereby providing Laurent polynomial expansions, in Pl\"ucker coordinates, for twisted web immanants for…

Combinatorics · Mathematics 2026-04-10 Esther Banaian , Elise Catania , Christian Gaetz , Miranda Moore , Gregg Musiker , Kayla Wright

Given a bounded strongly pseudoconvex domain $D$ in $\mathbb{C}^n$ with smooth boundary, we give a characterization through products of functions in weighted Bergman spaces of $(\lambda,\gamma)$-skew Carleson measures on $D$, with…

Complex Variables · Mathematics 2017-10-05 Marco Abate , Jasmin Raissy

A signed directed graph is a graph with sign and direction information on the edges. Even though signed directed graphs are more informative than unsigned or undirected graphs, they are more complicated to analyze and have received less…

Machine Learning · Computer Science 2023-02-17 Taewook Ko , Chong-Kwon Kim

An ordinal-valued metric taking its values in the set of all countable ordinals can be assigned to a metrizable set of nodes in a transfinite graph. Then, a variety of results concerning nodal eccentricities, radii, diameters, centers,…

Combinatorics · Mathematics 2007-05-23 A. H. Zemanian

Graphings are special bounded-degree graphs on probability spaces, representing limits of graph sequences that are convergent in a local or local-global sense. We describe a procedure for turning the underlying space into a compact metric…

Combinatorics · Mathematics 2021-02-17 László Lovász