Interval wavelets based multiscale normalizing flow for forecasting irregularly sampled time series (IWMNF)
This work addresses the problem of probabilistic forecasting of irregular multivariate time series (IMTS), a common scenario in domains such as healthcare, climate, and economics, characterized by heterogeneous sampling and missing values. Traditional statistical methods and deep learning techniques, although effective...