Twinning Complex Networked Systems: Data-Driven Calibration of the mABCD Synthetic Graph Generator

ArXi:2602.02044v2 Announce Type: replace-cross The increasing availability of relational data has contributed to a growing reliance on network-based representations of complex systems. Over time, these models have evolved to capture nuanced properties, such as the heterogeneity of relationships, leading to the concept of multilayer networks. However, the analysis and evaluation of methods for these structures is often hindered by the limited availability of large-scale empirical data. As a result, graph generators are commonly used as a workaround, albeit at the cost of