Graph neural networks (GNNs) are effective models for representation learning on relational
data. However, standard GNNs are limited in their expressive power, as they cannot …

Successful scientific applications of large-scale molecular dynamics often rely on automated
methods for identifying the local crystalline structure of condensed phases. Many existing …

The ability to faithfully represent real social networks is critical from the perspective of testing
various what-if scenarios which are not feasible to be implemented in a real system as the …

A simple quadrangulation of the sphere is a finite simple graph embedded on the sphere
such that every face is bounded by a walk of 4 edges. We consider the following classes of …

CaGe – a Virtual Environment for Studying Some Special Classes of Plane Graphs – an
Update Page 1 CaGe – a Virtual Environment for Studying Some Special Classes of Plane …

The Tammes problem is to find the arrangement of N points on a unit sphere which
maximizes the minimum distance between any two points. This problem is presently solved …

We describe an efficient new algorithm for the generation of fullerenes. Our implementation
of this algorithm is more than 3.5 times faster than the previously fastest generator for …

Fullerene graphs are cubic, 3-connected, planar graphs with exactly 12 pentagonal faces,
while all other faces are hexagons. Fullerene graphs are mathematical models of fullerene …

To test a graph's planarity in SAT-based graph generation we develop SAT encodings with
dynamic symmetry breaking as facilitated in the SAT modulo Symmetry (SMS) framework …

In this paper, we use theoretical and computational tools to continue our investigation of K 2
K_2‐hamiltonian graphs, that is, graphs in which the removal of any pair of adjacent vertices …