Network reconstruction and community detection from dynamics

Research output: Contribution to journalArticlepeer-review

75 Citations (SciVal)
136 Downloads (Pure)


We present a scalable nonparametric Bayesian method to perform network reconstruction from observed functional behavior that at the same time infers the communities present in the network. We show that the joint reconstruction with community detection has a synergistic effect, where the edge correlations used to inform the existence of communities are also inherently used to improve the accuracy of the reconstruction which, in turn, can better inform the uncovering of communities. We illustrate the use of our method with observations arising from epidemic models and the Ising model, both on synthetic and empirical networks, as well as on data containing only functional information.

Original languageEnglish
Article number128301
Pages (from-to)1-7
Number of pages7
JournalPhysical Review Letters
Issue number12
Publication statusPublished - 20 Sept 2019

Bibliographical note

8 pages, 5 figures


  • physics.soc-ph
  • cs.SI
  • stat.ML

ASJC Scopus subject areas

  • Physics and Astronomy(all)


Dive into the research topics of 'Network reconstruction and community detection from dynamics'. Together they form a unique fingerprint.

Cite this