How should I explain the difference between Generative Models and Configuration Models in Complex Networks in simple terms.
A generative model is a statistical model of the type P(G|t) that outputs a degree distribution based on its form and parameters [source] whereas a configuration model is a sequence of nodes with a fixed degree, that you can then randomly connect to create a network [source].
So you can use a generative model to create configuration models but you can't necessarily infer the generative model from the configuration model.