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Modelling neural probabilistic computation using vector symbolic architectures

Published:2023-12-16 Issue: Volume: Page:
ISSN:1871-4080
Container-title:Cognitive Neurodynamics
language:en
Short-container-title:Cogn Neurodyn

Author:

Furlong P. Michael^ORCID,Eliasmith Chris

Funder

Canada Research Chairs

Ontario Innovation Trust

Canada Foundation for Innovation

National Coordination Office

Neuro Research Charitable Trust

Air Force Office of Scientific Research

Intel Neuromorphic Research Community

Publisher

Springer Science and Business Media LLC

Subject

Cognitive Neuroscience

Link

https://link.springer.com/content/pdf/10.1007/s11571-023-10031-7.pdf

Reference94 articles.

1. Agarwal R, Chen Z, Sarma SV (2016) A novel nonparametric maximum likelihood estimator for probability density functions. IEEE Trans Pattern Anal Mach Intelligence 39(7):1294–1308

2. Anastasio TJ, Patton PE, Belkacem-Boussaid K (2000) Using Bayes’ rule to model multisensory enhancement in the superior colliculus. Neural Comput 12(5):1165–1187

3. Anderson CH, Van Essen DC (1994) Neurobiological computational systems. In: Computational intelligence imitating life 213222

4. Arimoto S (1977) Information measures and capacity of order $$\alpha $$ for discrete memoryless channels. Topics in information theory

5. Arora A, Furlong PM, Fitch R et al (2019) Multi-modal active perception for information gathering in science missions. Auton Robot 43(7):1827–1853

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