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Ne\v{s}et\v{r}il and Ossona de Mendez recently proposed a new definition of graph convergence called structural convergence. The structural convergence framework is based on the probability of satisfaction of logical formulas from a fixed…

Combinatorics · Mathematics 2023-09-07 David Hartman , Tomáš Hons , Jaroslav Nešetřil

Rewriting systems are often defined as binary relations over a given set of objects. This simple definition is used to describe various properties of rewriting such as termination, confluence, normal forms etc. In this paper, we introduce a…

Logic in Computer Science · Computer Science 2011-06-01 Dominique Duval , Rachid Echahed , Frédéric Prost

We present a categorical theory of monads and distributive laws in substructural contexts. In the study of distributive laws, the roles of (the absence of) structural rules for variable contexts have been recognized; our theory formalizes…

Logic in Computer Science · Computer Science 2026-05-14 Soichiro Fujii , Yun Chen Tsai , Yoàv Montacute , Ichiro Hasuo

We analytically explore the scaling properties of a general class of nested subgraphs in complex networks, which includes the $K$-core and the $K$-scaffold, among others. We name such class of subgraphs $K$-nested subgraphs due to the fact…

Disordered Systems and Neural Networks · Physics 2009-11-13 Bernat Corominas-Murtra , José F. F. Mendes , Ricard V. Solé

Conflict and dependency analysis is an important static analysis tool that provides an overview of the potential interactions of (graph) transformation rules. This analysis is based on critical pairs and initial conflicts, which represent…

Software Engineering · Computer Science 2026-05-07 Alexander Lauer , Jens Kosiol , Leen Lambers , Gabriele Taentzer

Most of the stochastic orders for comparing random variables, considered in the literature, are afflicted with two main drawbacks: (i) lack of connex property and (ii) lack of consideration of any dependence structure between the random…

Methodology · Statistics 2021-03-03 Sugata Ghosh , Asok K. Nanda

High-dimensional data analysis typically focuses on low-dimensional structure, often to aid interpretation and computational efficiency. Graphical models provide a powerful methodology for learning the conditional independence structure in…

Methodology · Statistics 2024-09-13 Maria De Iorio , Willem van den Boom , Alexandros Beskos , Ajay Jasra , Andrea Cremaschi

Established methods for structural elicitation typically rely on code modelling standard graphical models classes, most often Bayesian networks. However, more appropriate models may arise from asking the expert questions in common language…

Methodology · Statistics 2018-07-11 Rachel L. Wilkerson , Jim Q. Smith

In model-driven development, an ordered model transformation is a nested set of transformations between source and target classes, in which each transformation is governed by its own pre and post- conditions, but structurally dependent on…

Logic in Computer Science · Computer Science 2013-02-22 Maribel Fernández , Jeffrey Terrell

In this paper, we consider the structured perturbation analysis for multiple right-hand side linear systems with parameterized coefficient matrix. Especially, we present the explicit expressions for structured condition numbers for multiple…

Numerical Analysis · Mathematics 2019-10-15 Qingle Meng , Huaian Diao , Qinghua Yu

In this paper, we introduce the foundation of a fractal topological space constructed via a family of nested topological spaces endowed with subspace topologies, where the number of topological spaces involved in this family is related to…

General Mathematics · Mathematics 2021-07-13 Helene Porchon

We lay out an infinity categorical interpretation of reconstruction theorems which are germane to the symmetric monoidal perspective of noncommutative algebraic geometry, present sufficient conditions which allow for the factorization of…

Algebraic Topology · Mathematics 2025-07-18 Salash Tolan Nabaala

Graph rewrite formalisms are a powerful approach to modeling complex molecular systems. They capture the intrinsic concurrency of molecular interactions, thereby enabling a formal notion of mechanism (a partially ordered set of events) that…

Logic in Computer Science · Computer Science 2019-01-04 Ioana Cristescu , Walter Fontana , Jean Krivine

One goal of applied category theory is to better understand networks appearing throughout science and engineering. Here we introduce "structured cospans" as a way to study networks with inputs and outputs. Given a functor $L \colon…

Category Theory · Mathematics 2020-11-11 John C. Baez , Kenny Courser

A Random Graph is a random object which take its values in the space of graphs. We take advantage of the expressibility of graphs in order to model the uncertainty about the existence of causal relationships within a given set of variables.…

Artificial Intelligence · Computer Science 2026-04-30 Mauricio Gonzalez-Soto , Ivan R. Feliciano-Avelino , L. Enrique Sucar , Hugo J. Escalante Balderas

Connections between structural graph theory and finite model theory recently gained a lot of attention. In this setting, many interesting questions remain on the properties of dependent (NIP) hereditary classes of graphs, in particular…

Combinatorics · Mathematics 2026-01-01 Hector Buffière , Patrice Ossona de Mendez

In this paper we establish a link between fuzzy and preferential semantics for description logics and Self-Organising Maps, which have been proposed as possible candidates to explain the psychological mechanisms underlying category…

Artificial Intelligence · Computer Science 2022-02-07 Laura Giordano , Valentina Gliozzi , Daniele Theseider Dupré

A form-finding problem for tensegrity structures is studied; given an abstract graph, we show an algorithm to provide a necessary condition for it to be the underlying graph of a tensegrity in $\mathbb{R}^d$ (typically $d=2,3$) with…

Combinatorics · Mathematics 2020-07-21 Miguel de Guzmán , David Orden

Graphs are an essential part of many machine learning problems such as analysis of parse trees, social networks, knowledge graphs, transportation systems, and molecular structures. Applying machine learning in these areas typically involves…

Artificial Intelligence · Computer Science 2019-07-16 Mehdi Ben Lazreg , Morten Goodwin , Ole-Christoffer Granmo

This paper studies node classification in the inductive setting, i.e., aiming to learn a model on labeled training graphs and generalize it to infer node labels on unlabeled test graphs. This problem has been extensively studied with graph…

Machine Learning · Computer Science 2022-04-18 Meng Qu , Huiyu Cai , Jian Tang