Dimension reduction in vertex-weighted exponential random graphs

DOI10.1016/j.physa.2020.125289OpenAlexW3087543500WikidataQ115567825 ScholiaQ115567825MaRDI QIDQ2143327

Mei Yin, Ryan DeMuse

Publication date: 31 May 2022

Published in: Physica A (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1908.08565

zbMATH Keywords

stochastic block modelexponential random graphsvertex-weighted

Mathematics Subject Classification ID

Statistical mechanics, structure of matter (82-XX)

Cites Work

• Unnamed Item
• Unnamed Item
• Mixing time of exponential random graphs
• Representations for partially exchangeable arrays of random variables
• Global versus local asymptotic theories of finite-dimensional normed spaces
• Weighted exponential random graph models: scope and large network limits
• Exponential random graphs behave like mixtures of stochastic block models
• Decomposition of mean-field Gibbs distributions into product measures
• On the Lambert \(w\) function
• Mixing time of vertex-weighted exponential random graphs
• Inference in Ising models
• Estimating and understanding exponential random graph models
• Estimation in spin glasses: a first step
• An elementary proof of a theorem of Johnson and Lindenstrauss
• Random Graphs

This page was built for publication: Dimension reduction in vertex-weighted exponential random graphs