Problem: time series forecasting
Challenge: forecasting for non-stationary signals and multiple future steps prediction
?? how to deal with non-stationary datasets??
Introduction
one-step prediction problem VS multi-step prediction;
multi-step forecasting requires to accurately describe time series evolution.
limitation of the euclidean loss(MSE): in non-stationary context;
PP: Shape and time distortion loss for training deep time series forecasting models
原文：https://www.cnblogs.com/dulun/p/12292111.html