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Quantifying Synergistic Mutual Information

Griffith, Virgil and Koch, Christof (2014) Quantifying Synergistic Mutual Information. In: Guided Self-Organization: Inception. Emergence, Complexity and Computation. No.9. Springer Verlag , Berlin, pp. 159-190. ISBN 978-3-642-53733-2. https://resolver.caltech.edu/CaltechAUTHORS:20170622-070147683

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Abstract

Synergy is a fundamental concept in complex systems that has received much attention in computational biology (Narayanan et al. 2005; Balduzzi and Tononi 2008). Several papers (Schneidman et al. 2003a; Bell 2003; Nirenberg et al. 2001;Williams and Beer 2010) have proposed measures for quantifying synergy, but there remains no consensus which measure is most valid.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1007/978-3-642-53734-9_6DOIArticle
https://link.springer.com/chapter/10.1007%2F978-3-642-53734-9_6PublisherArticle
https://arxiv.org/abs/1205.4265arXivDiscussion Paper
ORCID:
AuthorORCID
Koch, Christof0000-0001-6482-8067
Additional Information:© 2014 Springer-Verlag Berlin Heidelberg. We thank Suzannah Fraker, Tracey Ho, Artemy Kolchinsky, Chris Adami, Giulio Tononi, Jim Beck, Nihat Ay, and Paul Williams for extensive discussions. This research was funded by the Paul G. Allen Family Foundation and a DOE CSGF fellowship to VG.
Funders:
Funding AgencyGrant Number
Paul G. Allen Family FoundationUNSPECIFIED
Department of Energy (DOE)UNSPECIFIED
Series Name:Emergence, Complexity and Computation
Issue or Number:9
Record Number:CaltechAUTHORS:20170622-070147683
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20170622-070147683
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:78449
Collection:CaltechAUTHORS
Deposited By: Ruth Sustaita
Deposited On:22 Jun 2017 18:07
Last Modified:03 Oct 2019 18:08

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