Autoregressive Point Processes as Latent State-Space Models: A Moment-Closure Approach to Fluctuations and Autocorrelations
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DOI: 10.1162/neco_a_01121
Abstract: Modeling and interpreting spike train data is a task of central importance in computational neuroscience, with significant translational implications. Two popular classes of data-driven models for this task are autoregressive point-process generalized linear models (PPGLM)… read more here.
Keywords: autoregressive point; latent state; state space; moment closure ... See more keywords