output
20192025
most citedExponential Random Graph models for Little Networks

45 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions

4 papers

physics.soc-ph2025

Using covariance of node states to design early warning signals for network dynamics

Shilong Yu, Neil G. MacLaren, Naoki Masuda

Real-life systems often experience regime shifts. An early warning signal (EWS) is a quantity that attempts to anticipate such a regime shift. Because complex systems of practical…

physics.soc-ph2024★ 4 cited

Observing network dynamics through sentinel nodes

Neil G. MacLaren, Baruch Barzel, Naoki Masuda

A fundamental premise of statistical physics is that the particles in a physical system are interchangeable, and hence the state of each specific component is representative of the…

eess.AS2020

Utterance Clustering Using Stereo Audio Channels

Yingjun Dong, Neil G. MacLaren, Yiding Cao +6

Utterance clustering is one of the actively researched topics in audio signal processing and machine learning. This study aims to improve the performance of utterance clustering by…

stat.ME2019★ 45 cited

Exponential Random Graph models for Little Networks

George G. Vega Yon, Andrew Slaughter, Kayla de la Haye

Statistical models for social networks have enabled researchers to study complex social phenomena that give rise to observed patterns of relationships among social actors and to ga…