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In recent years, graph prompting has emerged as a promising research direction, enabling the learning of additional tokens or subgraphs appended to the original graphs without requiring retraining of pre-trained graph models across various…

Machine Learning · Computer Science 2025-05-28 Qunzhong Wang , Xiangguo Sun , Hong Cheng

Graph neural networks are prominent models for representation learning over graph-structured data. While the capabilities and limitations of these models are well-understood for simple graphs, our understanding remains incomplete in the…

Machine Learning · Computer Science 2023-10-27 Xingyue Huang , Miguel Romero Orth , İsmail İlkan Ceylan , Pablo Barceló

Signal processing on graphs has received a lot of attention in the recent years. A lot of techniques have arised, inspired by classical signal processing ones, to allow studying signals on any kind of graph. A common aspect of these…

Information Theory · Computer Science 2016-05-18 Bastien Pasdeloup , Michael Rabbat , Vincent Gripon , Dominique Pastor , Grégoire Mercier

Two-sample tests utilizing a similarity graph on observations are useful for high-dimensional and non-Euclidean data due to their flexibility and good performance under a wide range of alternatives. Existing works mainly focused on sparse…

Statistics Theory · Mathematics 2023-11-14 Yejiong Zhu , Hao Chen

Given a graphical degree sequence ${\bf d}=(d_1,\ldots, d_n)$, let $G(n, {\bf d})$ denote a uniformly random graph on vertex set $[n]$ where vertex $ i$ has degree $d_i$ for every $1\le i\le n$. We give upper and lower bounds on the joint…

Combinatorics · Mathematics 2025-05-28 Pu Gao , Yuval Ohapkin

In this article we are introducing combinatorial spectra of graphs, this is a generalization of $H$-Hamiltonian spectra. The main motivation was to made from $H$-Hamiltonian spectra an operation and develop some algebra in this field. An…

Combinatorics · Mathematics 2023-11-21 Martin Dzúrik

If a vertex $v$ in a graph $G$ has degree larger than the average of the degrees of its neighbors, we call it a groupie in $G$. In the current work, we study the behavior of groupie in random multipartite graphs with the link probability…

Combinatorics · Mathematics 2012-09-18 Marius Portmann , Hongyun Wang

In this paper, various kinds of invariants of directed graphs are summarized. In the first topic, the invariant w(G) for a directed graph G is introduced, which is primarily defined by S. Chen and X.M. Chen to solve a problem of weak…

Combinatorics · Mathematics 2015-01-16 Sheng Chen , Yilong Zhang

We develop the Lie theory of Lie-admissible algebras whose product is enriched with higher operations modeled on directed graphs with a view to apply it to the deformation theories controlled by this kind of Lie algebras. We produce…

Quantum Algebra · Mathematics 2025-10-10 Ricardo Campos , Bruno Vallette

We discuss topological versions of the closed graph theorem, where continuity is inferred from near continuity in tandem with suitable conditions on source or target spaces. We seek internal characterizations of spaces satisfying a closed…

General Topology · Mathematics 2024-04-05 Dominikus Noll

We introduce and develop a theory of limits for sequences of sparse graphs based on $L^p$ graphons, which generalizes both the existing $L^\infty$ theory of dense graph limits and its extension by Bollob\'as and Riordan to sparse graphs…

Combinatorics · Mathematics 2019-08-19 Christian Borgs , Jennifer T. Chayes , Henry Cohn , Yufei Zhao

We prove that the class of chordal graphs is easily testable in the following sense. There exists a constant $c>0$ such that, if adding/removing at most $\epsilon n^2$ edges to a graph $G$ with $n$ vertices does not make it chordal, then a…

Combinatorics · Mathematics 2019-02-19 Rémi de Joannis de Verclos

The Union Closed Sets Conjecture is one of the most renowned problems in combinatorics. Its appeal lies in the simplicity of its statement contrasted with the potential complexity of its resolution. The conjecture posits that, in any union…

Combinatorics · Mathematics 2025-10-02 Nived J M

In this paper we introduce a novel polynomial-time algorithm to compute graph invariants based on the modified random walk idea on graphs. However not proved to be a full graph invariant by now, our method gives the right answer for the…

Data Structures and Algorithms · Computer Science 2015-08-24 Alexander Gamkrelidze , Gunter Hotz , Levan Varamashvili

Graph theory is a branch of mathematics in which pair-wise relations between objects are studied. My PhD thesis, supervised by David R. Wood, introduces and investigates a new family of graphs, called link graphs, that generalises the…

Combinatorics · Mathematics 2014-05-27 Bin Jia

In this paper, we study the task of detecting the edge dependency between two weighted random graphs. We formulate this task as a simple hypothesis testing problem, where under the null hypothesis, the two observed graphs are statistically…

Machine Learning · Computer Science 2024-09-25 Mor Oren , Vered Paslev , Wasim Huleihel

Mock threshold graphs are a simple generalization of threshold graphs that, like threshold graphs, are perfect graphs. Our main theorem is a characterization of mock threshold graphs by forbidden induced subgraphs. Other theorems…

Combinatorics · Mathematics 2021-06-16 Richard Behr , Vaidy Sivaraman , Thomas Zaslavsky

Let $G$ be a regular graph and $H$ a subgraph on the same vertex set. We give surprisingly compact formulas for the number of copies of $H$ one expects to find in a random subgraph of $G$.

Combinatorics · Mathematics 2025-06-26 Aaron Abrams , Rod Canfield , Andrew Granville

We study a weighted-set graph coloring problem in which one assigns $q$ colors to the vertices of a graph such that adjacent vertices have different colors, with a vertex weighting $w$ that either disfavors or favors a given subset of $s$…

Mathematical Physics · Physics 2011-08-19 Robert Shrock , Yan Xu

The covariance graph (aka bi-directed graph) of a probability distribution $p$ is the undirected graph $G$ where two nodes are adjacent iff their corresponding random variables are marginally dependent in $p$. In this paper, we present a…

Machine Learning · Statistics 2012-06-27 Jose M. Peña
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