Accurate forecasting of time series data is essential in many fields. However, real-world time series are often characterized by noise, non-stationarity and multiscale temporal dependencies, which ...

Time series forecasting finds extensive application across numerous real-world scenarios, yet faces challenges in modelling multi-period variability and exogenous variables. To address this, this ...