From statistical inference to a differential learning rule for stochastic neural networks

Stochastic neural networks are a prototypical computational device able to build a probabilistic representation of an ensemble of external stimuli. Building on the relationship between inference and learning, we derive a synaptic plasticity rule that relies only on delayed activity correlations, and...

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Detalles Bibliográficos
Autores principales: Saglietti, Luca, Gerace, Federica, Ingrosso, Alessandro, Baldassi, Carlo, Zecchina, Riccardo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2018
Materias:
Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6227809/
https://www.ncbi.nlm.nih.gov/pubmed/30443331
http://dx.doi.org/10.1098/rsfs.2018.0033

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6227809/
https://www.ncbi.nlm.nih.gov/pubmed/30443331
http://dx.doi.org/10.1098/rsfs.2018.0033

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