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We develop some aspects of a general theory of presentations of subshifts by labelled directed graphs, in particular by compact graphs. Also considered are synchronization properties of subshifts that lead to presentations by countable…

Dynamical Systems · Mathematics 2012-09-11 Wolfgang Krieger

This paper develops a structural theory of unique shortest paths in real-weighted graphs. Our main goal is to characterize exactly which sets of node sequences, which we call path systems, can be realized as unique shortest paths in a graph…

Data Structures and Algorithms · Computer Science 2018-10-18 Greg Bodwin

Directed graphs can be studied by their associated directed flag complex. The homology of this complex has been successful in applications as a topological invariant for digraphs. Through comparison with path homology theory, we derive a…

Algebraic Topology · Mathematics 2024-11-08 Thomas Chaplin , Heather A. Harrington , Ulrike Tillmann

In 2011, Penttila and Williford constructed an infinite new family of primitive $Q$-polynomial 3-class association schemes, not arising from distance regular graphs, by exploring the geometry of the lines of the unitary polar space…

Combinatorics · Mathematics 2020-09-08 Giusy Monzillo , Alessandro Siciliano

We give some illustrative applications of our recent result on decompositions of labelled complexes, including some new results on decompositions of hypergraphs with coloured or directed edges. For example, we give fairly general conditions…

Combinatorics · Mathematics 2020-04-22 Peter Keevash

Directed acyclic graphs provide a fundamental tool for representing directed dependence structures in multivariate network data, and are widely used to model financial and economic networks. However, accurate and interpretable estimation…

Methodology · Statistics 2026-05-26 Huihang Liu , Wenhui Li , Xinyu Zhang

Graph learning from data represents a canonical problem that has received substantial attention in the literature. However, insufficient work has been done in incorporating prior structural knowledge onto the learning of underlying…

Machine Learning · Statistics 2019-04-23 Sandeep Kumar , Jiaxi Ying , José Vinícius de M. Cardoso , Daniel Palomar

The assumed causal relationships depicted in a DAG are interpreted using a set of rules called D-separation rules. Although these rules can be implemented automatically using standard software, at least a basic understanding of their…

Methodology · Statistics 2025-02-20 Fernando Pires Hartwig , Timothy Feeney , Neil Davies

In this paper, we define several measures induced by a finite directed graph. The study themselves is interesting ont only in the noncommutative probability point of view but also in the algebraic structure point of view, since to define…

Probability · Mathematics 2007-05-23 Ilwoo Cho

It is known that families of graphs with a semialgebraic edge relation of bounded complexity satisfy much stronger regularity properties than arbitrary graphs, and that they can be decomposed into very homogeneous semialgebraic pieces up to…

Logic · Mathematics 2016-02-25 Artem Chernikov , Sergei Starchenko

We consider the normalized Laplace operator for directed graphs with positive and negative edge weights. This generalization of the normalized Laplace operator for undirected graphs is used to characterize directed acyclic graphs. Moreover,…

Combinatorics · Mathematics 2012-02-01 Frank Bauer

Separated graphs provide a powerful combinatorial tool for approximating dynamical systems. This paper details the explicit construction of Bratteli-like separated graphs -- a generalization of classical Bratteli diagrams -- that encode the…

Dynamical Systems · Mathematics 2026-03-17 Joan Claramunt

Bidirected graphs are a common generalisation of directed graphs where arcs can also be incoming to both their incident nodes, or outgoing from both their incident nodes. Such arcs allow a walk to change direction. Some algorithms can…

Data Structures and Algorithms · Computer Science 2026-05-14 Sebastian Schmidt , Juha Harviainen , Corentin Moumard , Aleksandr Politov , Francisco Sena , Alexandru I. Tomescu

Neural network models in neuroscience allow one to study how the connections between neurons shape the activity of neural circuits in the brain. In this chapter, we study Combinatorial Threshold-Linear Networks (CTLNs) in order to…

Neurons and Cognition · Quantitative Biology 2018-04-05 Katherine Morrison , Carina Curto

A general lack of understanding pertaining to deep feedforward neural networks (DNNs) can be attributed partly to a lack of tools with which to analyze the composition of non-linear functions, and partly to a lack of mathematical models…

Machine Learning · Computer Science 2022-06-14 Wen-Liang Hwang , Shih-Shuo Tung

We consider the problem of placing arrow heads in directed graph drawings without them overlapping other drawn objects. This gives drawings where edge directions can be deduced unambiguously. We show hardness of the problem, present exact…

Data Structures and Algorithms · Computer Science 2016-08-31 Carla Binucci , Markus Chimani , Walter Didimo , Giuseppe Liotta , Fabrizio Montecchiani

Directed acyclic graphs (DAGs) can be characterised as directed graphs whose strongly connected components are isolated vertices. Using this restriction on the strong components, we discover that when $m = cn$, where $m$ is the number of…

Combinatorics · Mathematics 2020-04-21 Élie de Panafieu , Sergey Dovgal

The paper constructs an infinite sequence of strongly regular directed graphs. The construction is based on representing adjacency matrices as block matrices composed of circulant blocks, together with the use of a compactification…

Combinatorics · Mathematics 2026-03-18 Viktor A. Byzov , Igor A. Pushkarev

We address the problem of merging graph and feature-space information while learning a metric from structured data. Existing algorithms tackle the problem in an asymmetric way, by either extracting vectorized summaries of the graph…

Machine Learning · Computer Science 2020-02-17 Nicolo Colombo

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