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cs.LG2026
PHAT: Modeling Period Heterogeneity for Multivariate Time Series Forecasting
Jiaming Ma, Qihe Huang, Haofeng Ma +6
While existing multivariate time series forecasting models have advanced significantly in modeling periodicity, they largely neglect the periodic heterogeneity common in real-world…
cs.LG2026
To See Far, Look Close: Evolutionary Forecasting for Long-term Time Series
Jiaming Ma, Siyuan Mu, Ruilin Tang +6
The prevailing Direct Forecasting (DF) paradigm dominates Long-term Time Series Forecasting (LTSF) by forcing models to predict the entire future horizon in a single forward pass.…
cs.LG2026
A General ReLearner: Empowering Spatiotemporal Prediction by Re-learning Input-label Residual
Jiaming Ma, Binwu Wang, Pengkun Wang +3
Prevailing spatiotemporal prediction models typically operate under a forward (unidirectional) learning paradigm, in which models extract spatiotemporal features from historical ob…