Results 111 to 120 of about 4,929,609 (209)

An edge sensitivity based gradient attack on graph isomorphic networks for graph classification problems

Scientific Reports
Abstract Graph Neural Networks have gained popularity over the past few years. Their ability to model relationships between entities of the same and different kind, represent molecules, model flow etc. have made them a go to tool for researchers.
Srinitish Srinivasan, Chandraumakantham OmKumar   +1 more
openaire   +3 more sources

Isomorphism versus commensurability for a class of finitely presented groups

, 2014
We construct a class of finitely presented groups where the isomorphism problem is solvable but the commensurability problem is unsolvable. Conversely, we construct a class of finitely presented groups within which the commensurability problem is ...
Arzhantseva, Goulnara, Minasyan, Ashot, Lafont, Jean-Francois   +2 more
core   +1 more source

Hybrid GNN-Based Link Prediction Model for Identifying Drug-Related Organized Crime Groups on Twitter

IEEE Access
In this paper, we propose a Graph Neural Network (GNN)-based link prediction model to analyze the interconnections of Drug-related Organized Crime Groups (DOCG) on X (formerly Twitter) and to identify their potential associations.
Eun-Young Park, Hyeon-Woo Lee, Jiyeon Kim   +2 more
doaj   +1 more source

Towards Faster Matrix Diagonalization with Graph Isomorphism Networks and the AlphaZero Framework

CoRR
In this paper, we introduce innovative approaches for accelerating the Jacobi method for matrix diagonalization, specifically through the formulation of large matrix diagonalization as a Semi-Markov Decision Process and small matrix diagonalization as a Markov Decision Process.
Geigh Zollicoffer, Kshitij Bhatta, Manish Bhattarai, Phil Romero, Christian F. A. Negre, Anders M. N. Niklasson, Adetokunbo Adedoyin   +6 more
openaire   +3 more sources

Graph Isomorphism Problem in Databases

, 2008
This project introduces history and basic notions of the graph theory. It describes graph theory problems, possible graph representations and practical graph management in databases. Aims to subgraph and graph isomorphism.
Stejskal, Roman
core  

A Data-Driven Graph Neural Network Framework for Predicting Topological Indices of Unicyclic and Bicyclic Graphs

Algorithms
Topological indices provide numerical descriptions of graph structure and support graph analysis in cheminformatics, network design, and graph mining.
Nadia Khan, Muhammad Zeeshan, Yousaf Iqbal, Mansoor Iqbal, Muhammad Amjad Iqbal, Sheraz Aslam   +5 more
doaj   +1 more source

p-GIN: a graph isomorphism network based on p-laplacian operator to enhance molecular property prediction

Discover Applied Sciences
Accurately predicting molecular properties is crucial in chemistry and materials science, as it facilitates faster discovery, minimizes experimental costs, and guides rational molecular design. While traditional quantum chemistry approaches remain widely
Jamshaid Ul Rahamn, Malik Ahsin Iqbal, Areen Rasool, Rongin Uwitije   +3 more
doaj   +1 more source

Edge-Centric Federated Subgraph Isomorphism Counting via Residual Graph Neural Networks

Information
Subgraph isomorphism counting is a fundamental yet computationally challenging task in graph analysis, with broad applications in bioinformatics and social network mining.
Jianjun Shi, Qinglong Wu, Xinming Zhang
doaj   +1 more source

Graph isomorphism for graph classes characterized by two forbidden induced subgraphs

, 2016
We study the complexity of the Graph Isomorphism problem on graph classes that are characterized by a finite number of forbidden induced subgraphs, focusing mostly on the case of two forbidden subgraphs.
Schweitzer, Pascal, Kratsch, Stefan
core   +1 more source

On Soft Graph Isomorphism

The soft set theory provides a flexible framework for dealing with uncertain and imprecise information that is not adequately handled by classical set theory.
Jinta Jose, Rajesh K. Thumbakara, Bobin George   +2 more
core   +1 more source