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Hierarchical structure and repetition are prevalent in graphs originating from nature or engineering. These patterns can be represented by a class of parametric-structure graphs, which are defined by templates that generate structure by way…

Data Structures and Algorithms · Computer Science 2020-11-16 Tal Ben-Nun , Lukas Gianinazzi , Torsten Hoefler , Yishai Oltchik

Categorical quantum mechanics and the Wolfram model offer distinct but complementary approaches to studying the relationship between diagrammatic rewriting systems over combinatorial structures and the foundations of physics; the objective…

Logic in Computer Science · Computer Science 2020-10-07 Jonathan Gorard , Manojna Namuduri , Xerxes D. Arsiwalla

Graphs, and graph transformation systems, are used in many areas within Computer Science: to represent data structures and algorithms, to define computation models, as a general modelling tool to study complex systems, etc. Research in term…

Symbolic Computation · Computer Science 2021-02-04 Patrick Bahr

In this paper we adapt previous work on rewriting string diagrams using hypergraphs to the case where the underlying category has a traced comonoid structure, in which wires can be forked and the outputs of a morphism can be connected to…

Logic in Computer Science · Computer Science 2026-01-14 Dan R. Ghica , George Kaye

Equality saturation, a technique for program optimisation and reasoning, has gained attention due to the resurgence of equality graphs (e-graphs). E-graphs represent equivalence classes of terms under rewrite rules, enabling simultaneous…

Logic in Computer Science · Computer Science 2025-05-05 Aleksei Tiurin , Dan R. Ghica , Nick Hu

It is natural for probabilistic programs to use conditionals to express alternative substructures in models, and loops (recursion) to express repeated substructures in models. Thus, probabilistic programs with conditionals and recursion…

Programming Languages · Computer Science 2020-10-26 David Chiang , Chung-chieh Shan

String theory and supersymmetry are theoretical ideas that go beyond the standard model of particle physics and show promise for unifying all forces. After a brief introduction to supersymmetry, we discuss the prospects for its experimental…

High Energy Physics - Theory · Physics 2008-11-26 John H. Schwarz , Nathan Seiberg

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

Large reasoning models (LRMs) generate complex reasoning traces with planning, reflection, verification, and backtracking. In this work, we introduce ReasoningFlow, a unified schema for analyzing the semantic structures of these complex…

Computation and Language · Computer Science 2025-06-04 Jinu Lee , Sagnik Mukherjee , Dilek Hakkani-Tur , Julia Hockenmaier

This tutorial gives an advanced introduction to string diagrams and graph languages for higher-order computation. The subject matter develops in a principled way, starting from the two dimensional syntax of key categorical concepts such as…

Logic in Computer Science · Computer Science 2024-12-05 Dan Ghica , Fabio Zanasi

Order diagrams are an important tool to visualize the complex structure of ordered sets. Favorable drawings of order diagrams, i.e., easily readable for humans, are hard to come by, even for small ordered sets. Many attempts were made to…

Computational Geometry · Computer Science 2023-12-29 Dominik Dürrschnabel , Tom Hanika , Gerd Stumme

We introduce an algebraic analogue of dynamical systems, based on term rewriting. We show that a recursive function applied to the output of an iterated rewriting system defines a formal class of models into which all the main architectures…

Category Theory · Mathematics 2023-11-07 Iolo Jones , Jerry Swan , Jeffrey Giansiracusa

Decision trees and systems of decision rules are widely used as classifiers, as a means for knowledge representation, and as algorithms. They are among the most interpretable models for data analysis. The study of the relationships between…

Artificial Intelligence · Computer Science 2023-05-04 Kerven Durdymyradov , Mikhail Moshkov

Many real-world phenomena are naturally modeled by graphs and networks. However, classical graph models are often limited to pairwise interactions and may not adequately capture the richer structures that arise in practice. Higher-order…

Social and Information Networks · Computer Science 2026-05-18 Takaaki Fujita , Florentin Smarandache

Knowledge graphs are an expressive and widely used data structure due to their ability to integrate data from different domains in a sensible and machine-readable way. Thus, they can be used to model a variety of systems such as molecules…

Neural and Evolutionary Computing · Computer Science 2023-08-28 Dominik Dold , Josep Soler Garrido , Victor Caceres Chian , Marcel Hildebrandt , Thomas Runkler

The representation of graphs is commonly based on the adjacency matrix concept. This formulation is the foundation of most algebraic and computational approaches to graph processing. The advent of deep learning language models offers a wide…

Artificial Intelligence · Computer Science 2025-12-16 Ezequiel Lopez-Rubio

I report on the development of a novel statistical mechanical formalism for the analysis of random graphs with many short loops, and processes on such graphs. The graphs are defined via maximum entropy ensembles, in which both the degrees…

Disordered Systems and Neural Networks · Physics 2016-05-04 A C C Coolen

For any given sequence of integers there exists a quantum field theory whose Feynman rules produce that sequence. An example is illustrated for the Stirling numbers. The method employed here offers a new direction in combinatorics and graph…

Quantum Physics · Physics 2013-09-13 Carl M. Bender , Dorje C. Brody , Bernhard K. Meister

Many systems comprising entities in interactions can be represented as graphs, whose structure gives significant insights about how these systems work. Network theory has undergone further developments, in particular in relation to…

Data Analysis, Statistics and Probability · Physics 2016-06-14 Ronan Hamon , Pierre Borgnat , Patrick Flandrin , Céline Robardet

Diagrams matter. Unfortunately, the deep learning community has no standard method for diagramming architectures. The current combination of linear algebra notation and ad-hoc diagrams fails to offer the necessary precision to understand…

Machine Learning · Computer Science 2024-02-09 Vincent Abbott