Representation of the structure of graphs by sequences of instructions

This article likely explores a novel approach to representing graph structures using sequences of instructions, potentially for use in machine learning or graph processing. The focus is on how to encode the complex relationships within a graph into a format that can be processed by algorithms or models. The use of 'instructions' suggests a procedural or programmatic approach to graph representation, which could offer advantages in terms of flexibility and expressiveness.