Graph pattern matching constitutes the identification of specific substructures within a larger network, a task of central importance across disciplines as diverse as social media analysis, ...

Matching preclusion examines the resilience of a network modelled as a graph by identifying the smallest set of edge removals that destroys all perfect matchings. Originating in the study of ...

Graph neural networks (GNNs) are a type of neural network architecture and deep learning method that can help users analyze graphs, enabling them to make predictions based on the data described by a ...