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Jonathan Pillow

2 accepted papers

2020

A general recurrent state space framework for modeling neural dynamics during decision-making

ICML 2020poster

An open question in systems and computational neuroscience is how neural circuits accumulate evidence towards a decision. Fitting models of decision-making theory to neural activity helps answer this question, but current approaches limit the number of these models that we can fit to neural data. He…

Cited by 51SourcePDFScholar
2020

Efficient Non-conjugate Gaussian Process Factor Models for Spike Count Data using Polynomial Approximations

ICML 2020poster

Gaussian Process Factor Analysis (GPFA) has been broadly applied to the problem of identifying smooth, low-dimensional temporal structure underlying large-scale neural recordings. However, spike trains are non-Gaussian, which motivates combining GPFA with discrete observation models for binned spike…

Cited by 23SourcePDFScholar