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Bayesian entropy estimation for binary spike train data using parametric prior knowledge
Published on 2014-11-072266 Views
Shannon's entropy is a basic quantity in information theory, and a fundamental building block for the analysis of neural codes. Estimating the entropy of a discrete distribution from samples is an imp
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Presentation
Bayesian entropy estimation for binary spike train data using parametric prior knowledge00:00
Bayesian approach01:07
Our approach01:56
Retinal Ganglion Cell data (1 ms bins)02:55