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Graphs and hypergraphs are foundational structures in discrete mathematics. They have many practical applications, including the rapidly developing field of bioinformatics, and more generally, biomathematics. They are also a source of…

Combinatorics · Mathematics 2019-01-16 Mark Budden , Josh Hiller , Andrew Penland

Existing foundation models, such as CLIP, aim to learn a unified embedding space for multimodal data, enabling a wide range of downstream web-based applications like search, recommendation, and content classification. However, these models…

Machine Learning · Computer Science 2025-04-28 Yufei He , Yuan Sui , Xiaoxin He , Yue Liu , Yifei Sun , Bryan Hooi

Hypergraphs generalize classical graphs by allowing a single edge to connect multiple vertices, providing a natural language for modeling higher-order interactions. Superhypergraphs extend this paradigm further by accommodating nested,…

Artificial Intelligence · Computer Science 2026-03-03 Takaaki Fujita , Florentin Smarandache

Polygraphs are a higher-dimensional generalization of the notion of directed graph. Based on those as unifying concept, this monograph on polygraphs revisits the theory of rewriting in the context of strict higher categories, adopting the…

Category Theory · Mathematics 2025-09-05 Dimitri Ara , Albert Burroni , Yves Guiraud , Philippe Malbos , François Métayer , Samuel Mimram

Graphs and various graph-like combinatorial structures, such as preorders and hypergraphs, are ubiquitous in programming. This paper focuses on representing graphs in a purely functional programming language like Haskell. There are several…

Programming Languages · Computer Science 2022-02-21 Andrey Mokhov

Embedding graphs in continous spaces is a key factor in designing and developing algorithms for automatic information extraction to be applied in diverse tasks (e.g., learning, inferring, predicting). The reliability of graph embeddings…

Machine Learning · Computer Science 2023-11-30 Andrea Marinoni , Pietro Lio' , Alessandro Barp , Christian Jutten , Mark Girolami

A network can be analyzed at different topological scales, ranging from single nodes to motifs, communities, up to the complete structure. We propose a novel intermediate-level topological analysis that considers non-overlapping subgraphs…

Computational Physics · Physics 2009-11-13 Lucas Antiqueira , Luciano da Fontoura Costa

Network theory has proven to be a powerful tool in describing and analyzing systems by modelling the relations between their constituent objects. In recent years great progress has been made by augmenting `traditional' network theory.…

Data Analysis, Statistics and Probability · Physics 2016-06-03 Dominik Traxl , Niklas Boers , Jürgen Kurths

We consider a framework for clustering edge-colored hypergraphs, where the goal is to cluster (equivalently, to color) objects based on the primary type of multiway interactions they participate in. One well-studied objective is to color…

Data Structures and Algorithms · Computer Science 2025-02-19 Alex Crane , Thomas Stanley , Blair D. Sullivan , Nate Veldt

Target class classification is a mixed classification and transition model whose integrated goal is to assign objects to a certain, so called target or normal class. The classification process is iterative, and in each step an object in a…

Machine Learning · Computer Science 2024-03-25 Levon Aslanyan , Hasmik Sahakyan

Temporal graphs are graphs whose topology is subject to discrete changes over time. Given a static underlying graph $G$, a temporal graph is represented by assigning a set of integer time-labels to every edge $e$ of $G$, indicating the…

Discrete Mathematics · Computer Science 2020-09-30 George B. Mertzios , Hendrik Molter , Rolf Niedermeier , Viktor Zamaraev , Philipp Zschoche

Graph minors are a primary tool in understanding the structure of undirected graphs, with many conceptual and algorithmic implications. We propose new variants of \emph{directed graph minors} and \emph{directed graph embeddings}, by…

Discrete Mathematics · Computer Science 2019-05-30 Argyrios Deligkas , Reshef Meir

The vast amount of data and increase of computational capacity have allowed the analysis of texts from several perspectives, including the representation of texts as complex networks. Nodes of the network represent the words, and edges…

Computation and Language · Computer Science 2017-11-09 Vanessa Q. Marinho , Graeme Hirst , Diego R. Amancio

We consider random labelings of finite graphs conditioned on a small fixed number of peaks. We introduce a continuum framework where a combinatorial graph is associated with a metric graph and edges are identified with intervals. Next we…

Probability · Mathematics 2017-08-15 Krzysztof Burdzy , Soumik Pal

For real application and theoretical investigation of ordinary hypergraphs and non-ordinary hypergraphs, researchers need to establish standard rules and feasible operating methods. We propose a visualization tool for investigating…

History and Overview · Mathematics 2025-03-27 Fei Ma , Bing Yao

Graphs are a representation of structured data that captures the relationships between sets of objects. With the ubiquity of available network data, there is increasing industrial and academic need to quickly analyze graphs with billions of…

Machine Learning · Computer Science 2023-07-28 Brandon Mayer , Anton Tsitsulin , Hendrik Fichtenberger , Jonathan Halcrow , Bryan Perozzi

Hypergraphs offer a natural modeling language for studying polyadic interactions between sets of entities. Many polyadic interactions are asymmetric, with nodes playing distinctive roles. In an academic collaboration network, for example,…

Physics and Society · Physics 2019-11-05 Philip Chodrow , Andrew Mellor

In this paper we study fundamental connectivity properties of hypergraphs from a graph-theoretic perspective, with the emphasis on cut edges, cut vertices, and blocks. To prepare the ground, we define various types of subhypergraphs, as…

Combinatorics · Mathematics 2015-05-29 M. Amin Bahmanian , Mateja Šajna

Graph embedding is a transformation of nodes of a network into a set of vectors. A good embedding should capture the underlying graph topology and structure, node-to-node relationship, and other relevant information about the graph, its…

Social and Information Networks · Computer Science 2021-12-02 Bogumił Kamiński , Łukasz Kraiński , Paweł Prałat , François Théberge

Twisted diagrams are "diagrams" with components in different categories. Structure maps are defined using auxiliary data which consists of functors relating the various categories to each other. Prime examples of the construction are…

Algebraic Topology · Mathematics 2008-05-28 Thomas Huettemann , Oliver Roendigs