SOFTS: Efficient Multivariate Time Series Forecasting with Series-Core Fusion

How SOFTS, a new MLP-based model with the innovative STar Aggregate-Dispatch (STAD) module, achieves state-of-the-art performance in multivariate time series forecasting with remarkable efficiency and scalability by reducing computational complexity from quadratic to linear.

I’m skipping the part to say “yay, time series is important but challenging! and …” which means I assume the reader knows the delicacy of Time Series forecasting and wants to absorb the core!

What does this …

art complexity computational core deep learning efficiency forecasting fusion linear machine learning mlp multivariate part performance research scalability series star state time series time-series-analysis time series forecasting