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Center for Nonlinear Studies |
The simplest way to build a random network is to add nodes and links so that each newly-introduced node is connected to a randomly chosen existing node. This process generates random recursive trees. In this talk, I will argue that many network models are simple generalizations of this basic process. I will also show how to compute characteristics of random networks using different combinatorial, probabilistic, and analytical tools. Along the way, we will see that sparse networks are usually self-averaging while the networks which become more and more dense substantially vary from realization to realization.
Host: Eli Bem-Naim