3 papers
cs.LG2026
Multivariate Time Series Forecasting needs Cross Variable Loss
Kuiye Ding, Yifan Hu, Hanchen Wang +1
Multivariate time series forecasting presents unique challenges because future variables often co-evolve under shared system dynamics. While existing studies mainly focus on cross-…
cs.LG2026
From Observations to States: Latent Time Series Forecasting
Jie Yang, Yifan Hu, Yuante Li +3
Deep learning has achieved strong performance in Time Series Forecasting (TSF). However, we identify a critical representation paradox, termed Latent Chaos: models with accurate pr…
cs.LG2026
Revisiting Multivariate Time Series Forecasting with Missing Values
Jie Yang, Yifan Hu, Kexin Zhang +3
Missing values are common in real-world time series, and multivariate time series forecasting with missing values (MTSF-M) has become a crucial area of research for ensuring reliab…