Discussion on "Sparse graphs using exchangeable random measures" by Francois Caron and Emily B. Fox
Mingyuan Zhou
TL;DR
This paper discusses the use of exchangeable random measures to model sparse graphs, highlighting their advantages and implications for statistical graph analysis.
Contribution
It provides a critical discussion on the methodology and applications of sparse graph models based on exchangeable random measures.
Findings
Exchangeable random measures effectively model sparse graphs.
The approach offers flexible and scalable graph representations.
Implications for future research in statistical network analysis.
Abstract
This is a discussion on "Sparse graphs using exchangeable random measures" by Francois Caron and Emily B. Fox, published in Journal of the Royal Statistical Society, Series B, 2017.
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Taxonomy
TopicsComplex Network Analysis Techniques · Stochastic processes and statistical mechanics · Bayesian Methods and Mixture Models