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We derive representation theorems for exchangeable distributions on finite and infinite graphs using elementary arguments based on geometric and graph-theoretic concepts. Our results elucidate some of the key differences, and their…

Statistics Theory · Mathematics 2018-09-18 Steffen L. Lauritzen , Alessandro Rinaldo , Kayvan Sadeghi

In this paper we show that classical notions from automata theory such as simulation and bisimulation can be lifted to the context of enriched categories. The usual properties of bisimulation are nearly all preserved in this new context.…

Logic in Computer Science · Computer Science 2007-05-23 Vincent Schmitt , Krzysztof Worytkiewicz

In this paper, we extend the ideas of graph pebbling to oriented graphs and find a classification for all graphs with fully traversable pebbling assignments that are isomorphic to their assignment graph. We then give some cases in which a…

Combinatorics · Mathematics 2022-03-02 Jared Glassband , Garrison Koch , Sophia Lebiere , Xufei Liu , Evan Sabini

Graph neural networks (GNNs) are typically applied to static graphs that are assumed to be known upfront. This static input structure is often informed purely by insight of the machine learning practitioner, and might not be optimal for the…

This paper generalizes Kocay's lemma, with particular applications to graph reconstruction, as well as discussing and proving aspects around the power of these generalizations and Kocay's original lemma, with a result on the reconstruction…

Combinatorics · Mathematics 2025-09-04 Peter Stark

We present a simple proof for the universality of invariant and equivariant tensorized graph neural networks. Our approach considers a restricted intermediate hypothetical model named Graph Homomorphism Model to reach the universality…

Machine Learning · Computer Science 2019-10-10 Takanori Maehara , Hoang NT

In this manuscript we develop a version of Szemer\'edi's regularity lemma that is suitable for analyzing multicolorings of complete graphs and directed graphs. In this, we follow the proof of Alon, Fischer, Krivelevich and M. Szegedy…

Combinatorics · Mathematics 2016-05-24 Maria Axenovich , Ryan R. Martin

To develop a preliminary understanding towards Graph Foundation Models, we study the extent to which pretrained Graph Neural Networks can be applied across datasets, an effort requiring to be agnostic to dataset-specific features and their…

Following the classical approach of Birkhoff, we suggest an enriched version of enriched universal algebra. Given a suitable base of enrichment $\mathcal V$, we define a language $\mathbb L$ to be a collection of $(X,Y)$-ary function…

Category Theory · Mathematics 2026-03-04 Jiří Rosický , Giacomo Tendas

Knowledge graphs have emerged as an important model for studying complex multi-relational data. This has given rise to the construction of numerous large scale but incomplete knowledge graphs encoding information extracted from various…

Machine Learning · Computer Science 2018-07-24 Rakshit Trivedi , Bunyamin Sisman , Jun Ma , Christos Faloutsos , Hongyuan Zha , Xin Luna Dong

We obtain several averaging lemmas for transport operator with a force term. These lemmas improve the regularity yet known by not considering the force term as part of an arbitrary right-hand side. Two methods are used: local variable…

Analysis of PDEs · Mathematics 2009-10-20 F. Berthelin , S. Junca

We show that weighted path orders are special instances of a variant of semantic path orders. Exploiting this fact, we introduce a generalization of weighted path orders that goes beyond the realm of simple termination. Experimental data…

Logic in Computer Science · Computer Science 2023-07-27 Teppei Saito , Nao Hirokawa

We provide an elementary proof of Y. Peres' lemma on the existence in certain dynamical systems of what we term heavy points, points whose ergodic averages consistently dominate the expected value of the ergodic averages. We also derive…

Dynamical Systems · Mathematics 2009-06-23 David Ralston

Szemeredi's Regularity Lemma is a very useful tool of extremal combinatorics. Recently, several refinements of this seminal result were obtained for special, more structured classes of graphs. We survey these results in their rich…

Combinatorics · Mathematics 2020-03-31 Yiting Jiang , Jaroslav Nesetril , Patrice Ossona de Mendez , Sebastian Siebertz

This paper discusses iterated monodromy groups for transcendental functions. We show that for every post-singularly finite entire transcendental function, the iterated monodromy action can be described by bounded activity automata of a…

Dynamical Systems · Mathematics 2022-10-20 Bernhard Reinke

We extend P\'olya's indicator diagram theory to encompass entire functions of order at most 1, allowing functions of maximal type. To do so, we introduce an extension of the complex plane in which indicator diagrams may be unbounded or even…

Complex Variables · Mathematics 2026-05-26 Kei Beauduin

We introduce and study so-called self-indexed graphs. These are (oriented) finite graphs endowed with a map from the set of edges to the set of vertices. Such graphs naturally arise from classical knot and link diagrams. In fact, the graphs…

Geometric Topology · Mathematics 2007-05-23 Matias Graña , Vladimir Turaev

A long standing open problem in extremal graph theory is to describe all graphs that maximize the number of induced copies of a path on four vertices. The character of the problem changes in the setting of oriented graphs, and becomes more…

Combinatorics · Mathematics 2020-06-12 Ilkyoo Choi , Bernard Lidický , Florian Pfender

Nominal automata models serve as a formalism for data languages, and in fact often relate closely to classical register models. The paradigm of name allocation in nominal automata helps alleviate the pervasive computational hardness of…

Logic in Computer Science · Computer Science 2026-02-11 Hannes Schulze , Lutz Schröder , Üsame Cengiz

Graph neural networks (GNNs) provide state-of-the-art results in a wide variety of tasks which typically involve predicting features at the vertices of a graph. They are built from layers of graph convolutions which serve as a powerful…

Machine Learning · Statistics 2024-11-08 Mauricio Velasco , Kaiying O'Hare , Bernardo Rychtenberg , Soledad Villar
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