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Gaussian process based nonlinear latent structure discovery in multivariate spike train data

A large body of recent work focuses on methods for extracting low-dimensional latent structure from multi-neuron spike train data. Most such methods employ either linear latent dynamics or linear mappings from latent space to log spike rates. Here we propose a doubly nonlinear latent variable model...

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Bibliografiska uppgifter
I publikationen:Adv Neural Inf Process Syst
Huvudupphovsmän: Wu, Anqi, Roy, Nicholas A., Keeley, Stephen, Pillow, Jonathan W.
Materialtyp: Artigo
Språk:Inglês
Publicerad: 2017
Ämnen:
Länkar:https://ncbi.nlm.nih.gov/pmc/articles/PMC6594561/
https://ncbi.nlm.nih.gov/pubmed/31244512
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