mlsanityData to 7 Oct 2026

Network reconstruction and community detection from dynamics

arXiv 1903.10833 ↗First posted 26 Mar 2019physics.soc-ph cs.SI physics.data-ancited by 13

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Abstract (arXiv)

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.

Key facts. Cited by 13 papers in the map (data through 7 Oct 2026). First posted on arXiv 26 Mar 2019.

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Citing papers per year: 2021: 3; 2022: 2; 2023: 3; 2024: 3; 2025: 2.

13 papers.

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  1. 2022Unifying Pairwise Interactions in Complex Dynamicscited by 8
  2. 2024Network reconstruction via the minimum description length principlecited by 5
  3. 2021Descriptive vs. inferential community detection in networks: pitfalls, myths, and half-truthscited by 3
  4. 2024Scalable network reconstruction in subquadratic timecited by 2
  5. 2023Community Detection with Known, Unknown, or Partially Known Auxiliary Latent Variablescited by 1
  6. 2023Module-based regularization improves Gaussian graphical models when observing noisy datacited by 1
  7. 2025Deep Graph Learning will stall without Network Sciencecited by 1
  8. 2025Uncertainty quantification and posterior sampling for network reconstructioncited by 1
  9. 2021Node metadata can produce predictability transitions in network inference problemscited by 0
  10. 2021Geodesic Length Distribution in Sparse Network Ensemblescited by 0
  11. 2022Bayesian Inference of Transition Matrices from Incomplete Graph Data with a Topological Priorcited by 0
  12. 2023Machine learning of network inference enhancement from noisy measurementscited by 0
1 more
  1. 2024Reconstructing networks from simple and complex contagionscited by 0