Abstract: As a promising strategy to achieve generalizable graph learning tasks, graph invariant learning emphasizes identifying invariant subgraphs for stable predictions on biased unknown ...

The possibility of developing a complete graph invariant computable in polynomial time remains an open question. Consequently, creating efficient algorithms to verify non-isomorphism, including ...

To date, it is unknown whether it is possible to construct a complete graph invariant in polynomial time, so fast algorithms for checking non-isomorphism are important, including heuristic algorithms, ...

With our GNN, we obtain the following results: green vertices are well paired vertices and red vertices are errors. Both graphs are now represented using the layout from the right above but the color ...

Abstract: In digital signal processing, a shift-invariant filter can be represented as a polynomial expansion of a shift operation, that is, the Z-transform representation. When extended to graph ...

Adding a graph in a spreadsheet is no big deal as long as you know the process. However, do you know that you can make a curved line graph in Excel or Google Sheets? If not, you should check out this ...

We study differential forms on an algebraic compactification of a moduli space of metric graphs. Canonical examples of such forms are obtained by pulling back invariant differentials along a tropical ...

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 ...