
PKU DistDF: OT Loss for Time Series Forecasting
Peking University’s Lin Zhouchen team proposes DistDF, a novel loss function using optimal transport to align joint distributions in time series forecasting, addressing MSE's independence bias. It converts conditional distribution matching to joint via Wasserstein distance, enabling reliable estimation. Accepted to ICLR 2026.






