Robert E Kass — accepted AI-conference papers

2020

Latent Dynamic Factor Analysis of High-Dimensional Neural Recordings

Heejong Bong, Zongge Liu, Zhao Ren, Matthew Smith, Valerie Ventura, Robert E Kass

NeurIPS 2020poster

High-dimensional neural recordings across multiple brain regions can be used to establish functional connectivity with good spatial and temporal resolution. We designed and implemented a novel method, Latent Dynamic Factor Analysis of High-dimensional time series (LDFA-H), which combines (a) a new a…

Cited by 15 Source ↗PDF ↗code ↗Scholar ↗

2016

A state-space model of cross-region dynamic connectivity in MEG/EEG

Ying Yang, Elissa Aminoff, Michael Tarr, Robert E Kass

NeurIPS 2016poster

Cross-region dynamic connectivity, which describes spatio-temporal dependence of neural activity among multiple brain regions of interest (ROIs), can provide important information for understanding cognition. For estimating such connectivity, magnetoencephalography (MEG) and electroencephalography (…

Cited by 34 Source ↗PDF ↗code ↗Scholar ↗