Bayesian temporal biclustering with applications to multi-subject neuroscience studies

arXiv:2406.17131v1 Announce Type: cross
Abstract: We consider the problem of analyzing multivariate time series collected on multiple subjects, with the goal of identifying groups of subjects exhibiting similar trends in their recorded measurements over time as well as time-varying groups of associated measurements. To this end, we propose a Bayesian model for temporal biclustering featuring nested partitions, where a time-invariant partition of subjects induces a time-varying partition of measurements. Our approach allows for data-driven determination of the number of subject …

abstract applications arxiv bayesian cs.lg multi multiple multivariate neuroscience problem series stat.ap stat.me studies temporal time series trends type