Published 2014
| Version Submitted
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Quantifying Synergistic Mutual Information
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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.
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.Attached Files
Submitted - 1205.4265.pdf
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1205.4265.pdf
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- Eprint ID
- 78449
- DOI
- 10.1007/978-3-642-53734-9_6
- Resolver ID
- CaltechAUTHORS:20170622-070147683
Related works
- Describes
- https://arxiv.org/abs/1205.4265 (URL)
Funding
- Paul G. Allen Family Foundation
- Department of Energy (DOE)
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- Created
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2017-06-22Created from EPrint's datestamp field
- Updated
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2021-11-15Created from EPrint's last_modified field
Caltech Custom Metadata
- Series Name
- Emergence, Complexity and Computation
- Series Volume or Issue Number
- 9