We investigate the interplay between the graph isomorphism problem, logical definability, and structural graph theory on a rich family of dense graph classes: graph classes of bounded rank width. We ...

The results We found that the Logistic Regression model achieved 66% accuracy in determining isomorphism while the neural network models achieved 99.9% accuracy. The almost perfect prediction ...

The graph isomorphism problem remains one of those mysteries in theoretical computer science that fascinates laypersons and experts alike. In 1979, Garey and Johnson mentioned the problem in their ...

Discussions Scott is a python library to compute, for any fully-labelled (edge and node) graph, a canonical tree representative of its isomorphism class, that can be derived into a canonical trace ...

Graph isomorphism is an essential problem in graph theory and widely used in a variety of applications. With graph size increasing, graph isomorphism become difficult for classical computation since ...

We propose a new approach to solve graph isomorphism using parameterized matching. To find isomorphism between two graphs, one graph is linearized, i.e., represented as a graph walk that covers all ...

We prove that for friendly graphs, the convex relaxation is guaranteed to find the exact isomorphism or certify its inexistence. This result is further extended to approximately isomorphic graphs, for ...