What makes a small-world network? Leveraging machine learning for the robust prediction and classification of networks

arXiv:2403.13215v1 Announce Type: cross
Abstract: The ability to simulate realistic networks based on empirical data is an important task across scientific disciplines, from epidemiology to computer science. Often simulation approaches involve selecting a suitable network generative model such as Erd\"os-R\'enyi or small-world. However, few tools are available to quantify if a particular generative model is suitable for capturing a given network structure or organization. We utilize advances in interpretable machine learning to classify simulated networks by our generative models based …

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