The author proposes iTransformer as an inverted structure of Transformer, focusing on capturing multivariate correlations and learning series representations efficiently. Experimentally, iTransformer achieves state-of-the-art performance in time series forecasting.
Inverting the Transformer structure enhances time series forecasting by capturing multivariate correlations and improving series representations.