English
Related papers

Related papers: Logarithmic Weisfeiler-Leman Identifies All Planar…

200 papers

Consider property testing on bounded degree graphs and let $\varepsilon>0$ denote the proximity parameter. A remarkable theorem of Newman-Sohler (SICOMP 2013) asserts that all properties of planar graphs (more generally hyperfinite) are…

Data Structures and Algorithms · Computer Science 2024-05-10 Sabyasachi Basu , Akash Kumar , C. Seshadhri

We present a deterministic way of assigning small (log bit) weights to the edges of a bipartite planar graph so that the minimum weight perfect matching becomes unique. The isolation lemma as described in (Mulmuley et al. 1987) achieves the…

Data Structures and Algorithms · Computer Science 2008-02-21 Samir Datta , Raghav Kulkarni , Sambuddha Roy

A hypergraph consists of a set of nodes along with a collection of subsets of the nodes called hyperedges. Higher-order link prediction is the task of predicting the existence of a missing hyperedge in a hypergraph. A hyperedge…

Machine Learning · Computer Science 2024-12-04 Simon Zhang , Cheng Xin , Tamal K. Dey

The Graph Isomorphism problem has both theoretical and practical interest. In this paper we present an algorithm, called conauto-1.2, that efficiently tests whether two graphs are isomorphic, and finds an isomorphism if they are. This…

Data Structures and Algorithms · Computer Science 2011-06-23 Jose Luis Lopez-Presa , Antonio Fernandez Anta

A graph neural network (GNN) is a good choice for predicting the chemical properties of molecules. Compared with other deep networks, however, the current performance of a GNN is limited owing to the "curse of depth." Inspired by…

Machine Learning · Computer Science 2020-08-19 Katsuhiko Ishiguro , Kenta Oono , Kohei Hayashi

We formulate an XAI-based model improvement approach for Graph Neural Networks (GNNs) for node classification, called Explanation Enhanced Graph Learning (EEGL). The goal is to improve predictive performance of GNN using explanations. EEGL…

Machine Learning · Computer Science 2024-03-13 Harish G. Naik , Jan Polster , Raj Shekhar , Tamás Horváth , György Turán

We give an algorithm that, for every fixed k, decides isomorphism of graphs of rank width at most k in polynomial time. As the clique width of a graph is bounded in terms of its rank width, we also obtain a polynomial time isomorphism test…

Discrete Mathematics · Computer Science 2015-05-15 Martin Grohe , Pascal Schweitzer

While Graph Neural Networks (GNNs) have achieved remarkable results in a variety of applications, recent studies exposed important shortcomings in their ability to capture the structure of the underlying graph. It has been shown that the…

Machine Learning · Computer Science 2023-09-26 Giorgos Bouritsas , Fabrizio Frasca , Stefanos Zafeiriou , Michael M. Bronstein

We initiate the study of computational problems on $k$-mers (strings of length $k$) in labeled graphs. As a starting point, we consider the problem of counting the number of distinct $k$-mers found on the walks of a graph. We establish that…

Data Structures and Algorithms · Computer Science 2026-02-23 Jarno N. Alanko , Maximo Perez-Lopez

In this paper we show lower bounds for a certain large class of algorithms solving the Graph Isomorphism problem, even on expander graph instances. Spielman [25] shows an algorithm for isomorphism of strongly regular expander graphs that…

Computational Complexity · Computer Science 2016-10-31 Aaron Snook , Grant Schoenebeck , Paolo Codenotti

In this paper, we present two main results. First, by only one conjecture (Conjecture 2.9) for recognizing a vertex symmetric graph, which is the hardest task for our problem, we construct an algorithm for finding an isomorphism between two…

Data Structures and Algorithms · Computer Science 2017-06-29 Caishi Fang

Graph matching, also known as network alignment, refers to finding a bijection between the vertex sets of two given graphs so as to maximally align their edges. This fundamental computational problem arises frequently in multiple fields…

Data Structures and Algorithms · Computer Science 2021-08-10 Cheng Mao , Mark Rudelson , Konstantin Tikhomirov

We establish an isomorphism between the Grothendieck-Teichm\"uller Lie algebra $\mathfrak{grt}_1$ in depth two modulo higher depth and the cohomology of the two-loop part of the graph complex of internally connected graphs…

Quantum Algebra · Mathematics 2017-07-04 Matteo Felder

Graph Neural Networks (GNNs) face fundamental limitations in expressivity and capturing structural heterogeneity. Standard message-passing architectures are constrained by the 1-dimensional Weisfeiler-Leman (1-WL) test, unable to…

Machine Learning · Computer Science 2026-05-19 Asela Hevapathige , Ahad N. Zehmakan , Asiri Wijesinghe , Saman Halgamuge

We systematically investigate the complexity of counting subgraph patterns modulo fixed integers. For example, it is known that the parity of the number of $k$-matchings can be determined in polynomial time by a simple reduction to the…

Computational Complexity · Computer Science 2021-07-02 Radu Curticapean , Holger Dell , Thore Husfeldt

Two graphs $G$ and $H$ are homomorphism indistinguishable over a family of graphs $\mathcal{F}$ if for all graphs $F \in \mathcal{F}$ the number of homomorphisms from $F$ to $G$ is equal to the number of homomorphism from $F$ to $H$. Many…

Logic in Computer Science · Computer Science 2024-02-15 Tim Seppelt

The cyclability of a graph is the maximum integer $k$ for which every $k$ vertices lie on a cycle. The algorithmic version of the problem, given a graph $G$ and a non-negative integer $k,$ decide whether the cyclability of $G$ is at least…

Combinatorics · Mathematics 2016-01-26 Petr A. Golovach , Marcin Kamiński , Spyridon Maniatis , Dimitrios M. Thilikos

Numerous recent works have analyzed the expressive power of message-passing graph neural networks (MPNNs), primarily utilizing combinatorial techniques such as the $1$-dimensional Weisfeiler-Leman test ($1$-WL) for the graph isomorphism…

Machine Learning · Computer Science 2023-11-03 Jan Böker , Ron Levie , Ningyuan Huang , Soledad Villar , Christopher Morris

Various recent proposals increase the distinguishing power of Graph Neural Networks GNNs by propagating features between $k$-tuples of vertices. The distinguishing power of these "higher-order'' GNNs is known to be bounded by the…

Machine Learning · Computer Science 2021-06-15 Pablo Barceló , Floris Geerts , Juan Reutter , Maksimilian Ryschkov

In this paper, we introduce and study the multilevel-planarity testing problem, which is a generalization of upward planarity and level planarity. Let $G = (V, E)$ be a directed graph and let $\ell: V \to \mathcal P(\mathbb Z)$ be a…

Data Structures and Algorithms · Computer Science 2018-11-01 Lukas Barth , Guido Brückner , Paul Jungeblut , Marcel Radermacher