Dynamic Linear Coregionalization for Realistic Synthetic Multivariate Time Series

arXiv:2604.05064v2 Announce Type: replace-cross Abstract: Synthetic data is essential for training foundation models for time series (FMTS), but most generators assume static correlations, and are typically missing realistic inter-channel dependencies. We introduce DynLMC, a Dynamic Linear Model of...