Exploration of synergistic and redundant information sharing in static and dynamical Gaussian systems
- Submitting institution
-
University of Sussex
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 156234_59952
- Type
- D - Journal article
- DOI
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10.1103/PhysRevE.91.052802
- Title of journal
- Physical Review E
- Article number
- a052802
- First page
- -
- Volume
- 91
- Issue
- 5
- ISSN
- 1539-3755
- Open access status
- Out of scope for open access requirements
- Month of publication
- May
- Year of publication
- 2015
- URL
-
https://doi.org/10.1103/PhysRevE.91.052802
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
0
- Research group(s)
-
-
- Citation count
- 63
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- "This paper triggered invitations to present at two international workshops, because it represented a significant advance in the field, both theoretical and applied: (i) “Workshop on Neural Information Dynamics, Causality and Computation near Criticality [1]”, Frankfurt Institute for Advanced Studies, 2014; (ii) “Basque Center for Applied Mathematics Workshop in Quantitative Biomedicine for Health and Disease [2]”, Bilbao, 2015. The paper is well cited, prominently from works on dynamical complexity in the cardiovascular and cardiorespiratory systems, (e.g., in [3]) and further work on multivariate information decompositions [4,5].
[1] https://compneuroweb.com/workshops.html
[2] http://www.bcamath.org/en/workshops/quantitative-biomedicine-2015
[3] https://doi.org/10.1007/978-3-319-58709-7_3
[4] https://doi.org/10.1103/PhysRevLett.116.238701
[5] https://doi.org/10.1103/PhysRevE.100.032305"
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -