Evaluating Sequence Assembly Strategies for Differentially Private Synthetic Time-Series Forecasting

Differentially private time-series generators commonly produce fixed-length synthetic windows, whereas downstream forecasting models often require long continuous training sequences. How these windows are assembled after generation can therefore alter the effective synthetic data presented to a fore