Efficient non-conjugate Gaussian process factor models for spike count data using polynomial approximationsJan 1, 2020·Stephen Keeley,David Zoltowski,Yiyi Yu,Spencer Smith,Jonathan Pillow· 0 min read CiteTypeConference paperPublicationInternational conference on machine learningLast updated on Oct 18, 2024 ← A general recurrent state space framework for modeling neural dynamics during decision-making Jan 1, 2020Modeling statistical dependencies in multi-region spike train data Jan 1, 2020 →