New paper on arXiv: Decomposition of mean-field Gibbs distributions into product measures

I’m happy to say that my advisor Ronen Eldan and I recently uploaded a paper to the arXiv under the title “Decomposition of mean-fields Gibbs distributions into product measures” (https://arxiv.org/abs/1708.05859). This is a sister paper of the previous one about exponential random graphs: this one presents a “general framework” and only briefly touches on how … More New paper on arXiv: Decomposition of mean-field Gibbs distributions into product measures

Random graphs: The exponential random graph model

Some mathematicians like probability, and some mathematicians like graphs, so it’s only natural that some mathematicians like probabilistic graphs. That is, they like to generate graphs at random, and then ask all sorts of questions about them: What are the features of a random graph? Will it be connected? Will it contain many triangles? Will … More Random graphs: The exponential random graph model

Random graphs: The Erdős–Rényi G(n,p) model

Some mathematicians like probability, and some mathematicians like graphs, so it’s only natural that some mathematicians like probabilistic graphs. That is, they like to generate graphs at random, and then ask all sorts of questions about them: What are the features of a random graph? Will it be connected? Will it contain many triangles? Will … More Random graphs: The Erdős–Rényi G(n,p) model

New paper on arXiv: Exponential random graphs behave like mixtures of stochastic block models

In recent years, there has been an increasing interest in academic papers whose opening paragraphs describe the increasing interest in the (increasingly common) field of network theory. From mathematicians to sociologists, many a great scientist have written introductory paragraphs on this interesting explosion. For example: Chatterjee and Diaconis (2013): Bhamidi, Bresler and Sly (2011): Yan, … More New paper on arXiv: Exponential random graphs behave like mixtures of stochastic block models