Revealing physical interaction networks from statistics of collective dynamics

@inproceedings{Nitzan2017RevealingPI,
  title={Revealing physical interaction networks from statistics of collective dynamics},
  author={Mor Nitzan and Jose Casadiego and Marc Timme},
  booktitle={Science Advances},
  year={2017}
}
Revealing physical interactions in complex systems from observed collective dynamics constitutes a fundamental inverse problem in science. Current reconstruction methods require access to a system’s model or dynamical data at a level of detail often not available. We exploit changes in invariant measures, in particular distributions of sampled states of the system in response to driving signals, and use compressed sensing to reveal physical interaction networks. Dynamical observations following… CONTINUE READING
Recent Discussions
This paper has been referenced on Twitter 62 times over the past 90 days. VIEW TWEETS

From This Paper

Figures, tables, and topics from this paper.
5 Citations
48 References
Similar Papers

References

Publications referenced by this paper.
Showing 1-10 of 48 references

Network topology inference from infection statistics

  • I. Tomovski, L. Kocarev
  • Phys. A 436,
  • 2015

Untangling brainwide dynamics in consciousness by crossembedding

  • M. Timme
  • PLOS Comput . Biol .
  • 2015

coli proteome and transcriptome with single - molecule sensitivity in single cells

  • P. J. Choi, G.-W. Li, +5 authors E. Quantifying
  • Science
  • 2015

CVX: Matlab Software for Disciplined Convex Programming, Version 2.1 (CVX Research, 2014); http://cvxr.com/cvx

  • M. Grant, S. Boyd
  • 2014
1 Excerpt

Similar Papers

Loading similar papers…