Interpreting recurrent neural networks behaviour via excitable network attractors
- Submitting institution
-
University of Exeter
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 6406
- Type
- D - Journal article
- DOI
-
10.1007/s12559-019-09634-2
- Title of journal
- Cognitive Computation
- Article number
- 2
- First page
- -
- Volume
- 12
- Issue
- 2
- ISSN
- 1866-9956
- Open access status
- Compliant
- Month of publication
- March
- Year of publication
- 2019
- URL
-
-
- 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
- No
- Number of additional authors
-
2
- Research group(s)
-
-
- Citation count
- 5
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper is the output of a successful interdisciplinary collaboration between computer science and mathematics faculty at the University of Exeter. The paper has been well received by the community and resulted in an invitation to give a one hour invited talk at the V Workshop on Dynamical Systems and Brain-Inspired Information Processing in Konstanz (July 2019). Based on this work, we have produced another paper published in the 2020 special issue at Physica D, Elsevier (https://doi.org/10.1016/j.physd.2020.132609).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -