Understanding Interdependency Through Complex Information Sharing

  title={Understanding Interdependency Through Complex Information Sharing},
  author={Fernando Rosas and Vasilis Ntranos and Christopher J. Ellison and Sofie Pollin and Marian Verhelst},
The interactions between three or more random variables are often nontrivial, poorly understood, and yet, are paramount for future advances in fields such as network information theory, neuroscience, genetics and many others. In this work, we propose to analyze these interactions as different modes of information sharing. Towards this end, we introduce a novel axiomatic framework for decomposing the joint entropy, which characterizes the various ways in which random variables can share… CONTINUE READING
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Exploration of synergistic and redundant information sharing in static and dynamical gaussian systems

  • A. B. Barrett
  • Physical Review E, vol. 91, no. 5, p. 052802…
  • 2015
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Understanding high-order correlations using a synergybased decomposition of the total entropy

  • F. Rosas, V. Ntranos, C. J. Ellison, M. Verhelst, S. Pollin
  • Proceedings of the 5th joint WIC/IEEE Symposium…
  • 2015
1 Excerpt

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