arXiv (OAI Expanded)
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Latent kinetic Ising models of neural spike trains
Inferring directed effective interactions from neuronal spike trains is a central inverse problem in statistical physics and computational neuroscience. Kinetic Ising models provide a tractable framework for this task, but their application to neural data typically requires binning spike trains into
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