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The theory of graphons is an important tool in understanding properties of large networks. We investigate a power-law random graph model and cast it in the graphon framework. The distinctively different structures of the limit graph are…

Probability · Mathematics 2022-08-22 Mei Yin

We prove a central limit theorem for a certain class of functions on sparse rank-one inhomogeneous random graphs endowed with additional i.i.d. edge and vertex weights. Our proof of the central limit theorem uses a perturbative form of…

Probability · Mathematics 2024-04-22 Anja Sturm , Moritz Wemheuer

The theory of graph limits is only understood to any nontrivial degree in the cases of dense graphs and of bounded degree graphs. There is, however, a lot of interest in the intermediate cases. It appears that the most important…

Combinatorics · Mathematics 2021-02-17 Laszlo Lovasz

In recent work by Johnson et al. (2022), a framework was described for the study of graph problems over classes specified by omitting each of a finite set of graphs as subgraphs. If a problem falls into the framework then its computational…

Computational Complexity · Computer Science 2025-03-17 Tala Eagling-Vose , Barnaby Martin , Daniel Paulusma , Siani Smith

Graphs drawn in the plane are ubiquitous, arising from data sets through a variety of methods ranging from GIS analysis to image classification to shape analysis. A fundamental problem in this type of data is comparison: given a set of such…

Computational Geometry · Computer Science 2022-10-20 Levent Batakci , Abigail Branson , Bryan Castillo , Candace Todd , Erin Wolf Chambers , Elizabeth Munch

Motivated by the work of Lov\'asz and Szegedy on the convergence and limits of dense graph sequences, we investigate the convergence and limits of finite trees with respect to sampling in normalized distance. Based on separable real trees,…

Combinatorics · Mathematics 2021-10-19 Gábor Elek , Gábor Tardos

We study the relation between the growth rate of a graph property and the entropy of the graph limits that arise from graphs with that property. In particular, for hereditary classes we obtain a new description of the colouring number,…

Combinatorics · Mathematics 2013-12-20 Hamed Hatami , Svante Janson , Balázs Szegedy

In this paper, we provide a general framework for counting geometric structures in pseudo-random graphs. As applications, our theorems recover and improve several results on the finite field analog of questions originally raised in the…

Combinatorics · Mathematics 2025-04-30 Thang Pham , Steven Senger , Michael Tait , Vu Thi Huong Thu

In this work, we translate at the level of decorated trees some of the crucial arguments which have been used in arXiv:2112.10739 for proposing a diagram-free approach for the convergence of the model in Regularity Structures. This allows…

Probability · Mathematics 2023-10-05 Yvain Bruned , Usama Nadeem

We study first-order model checking, by which we refer to the problem of deciding whether or not a given first-order sentence is satisfied by a given finite structure. In particular, we aim to understand on which sets of sentences this…

Logic in Computer Science · Computer Science 2014-07-15 Hubie Chen

This paper studies the structure of graphs with given tree-width and excluding a fixed complete bipartite subgraph, which generalises the bounded degree setting. We give a new structural description of such graphs in terms of so-called…

Combinatorics · Mathematics 2025-12-15 Chun-Hung Liu , David R. Wood

We define and study a natural category of graph limits. The objects are pairs $(\pi,\mu)$, where $\pi$ (the distribution of vertices) is an abstract probability measure on some abstract measurable space $(X,\mathcal{A})$ and $\mu$ (the…

Combinatorics · Mathematics 2026-03-04 Martin Doležal , Wiesław Kubiś

Learning a graph with a specific structure is essential for interpretability and identification of the relationships among data. It is well known that structured graph learning from observed samples is an NP-hard combinatorial problem. In…

Machine Learning · Statistics 2019-09-26 Sandeep Kumar , Jiaxi Ying , Jos'e Vin'icius de M. Cardoso , Daniel P. Palomar

We consider a generalisation of the classical Ramsey theory setting to a setting where each of the edges of the underlying host graph is coloured with a {\em set} of colours (instead of just one colour). We give bounds for monochromatic…

Combinatorics · Mathematics 2018-05-30 Sebastián Bustamante , Maya Stein

A generic method for combinatorial constructions of intrinsic geometrical spaces is presented. It is based on the well known inverse sequences of finite graphs that determine (in the limit) topological spaces. If a pattern of the…

Computational Geometry · Computer Science 2020-10-09 Stanislaw Ambroszkiewicz

The colored neighborhood metric for sparse graphs was introduced by Bollob\'as and Riordan. The corresponding convergence notion refines a convergence notion introduced by Benjamini and Schramm. We prove that even in this refined sense, the…

Combinatorics · Mathematics 2013-08-23 Hamed Hatami , László Lovász , Balázs Szegedy

In the field of parameterized complexity theory, the study of graph width measures has been intimately connected with the development of width-based model checking algorithms for combinatorial properties on graphs. In this work, we…

Data Structures and Algorithms · Computer Science 2026-05-21 Mateus de Oliveira Oliveira , Sam Urmian

We show that for any fixed dense graph G and bounded-degree tree T on the same number of vertices, a modest random perturbation of G will typically contain a copy of T . This combines the viewpoints of the well-studied problems of embedding…

Combinatorics · Mathematics 2025-05-30 Michael Krivelevich , Matthew Kwan , Benny Sudakov

Gromov asked what a typical (finitely presented) group looks like, and he suggested a way to make the question precise in terms of limiting density. The typical finitely generated group is known to share some important properties with the…

Logic · Mathematics 2022-09-12 Johanna N. Y. Franklin , Meng-Che "Turbo" Ho , Julia Knight

In this work, we consider an extension of graphical models to random graphs, trees, and other objects. To do this, many fundamental concepts for multivariate random variables (e.g., marginal variables, Gibbs distribution, Markov properties)…

Machine Learning · Statistics 2017-05-08 Neil Hallonquist