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Bayesian Inference for Generalized Linear Models for Spiking Neurons

Generalized Linear Models (GLMs) are commonly used statistical methods for modelling the relationship between neural population activity and presented stimuli. When the dimension of the parameter space is large, strong regularization has to be used in order to fit GLMs to datasets of realistic size...

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Bibliografische gegevens
Hoofdauteurs: Gerwinn, Sebastian, Macke, Jakob H., Bethge, Matthias
Formaat: Artigo
Taal:Inglês
Gepubliceerd in: Frontiers Research Foundation 2010
Onderwerpen:
Online toegang:https://ncbi.nlm.nih.gov/pmc/articles/PMC2889714/
https://ncbi.nlm.nih.gov/pubmed/20577627
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fncom.2010.00012
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