2 papers
physics.ao-ph2026
SOON: Symmetric Orthogonal Operator Network for Global Subseasonal-to-Seasonal Climate Forecasting
Ziyu Zhou, Tian Zhou, Shiyu Wang +2
Accurate global Subseasonal-to-Seasonal (S2S) climate forecasting is critical for disaster preparedness and resource management, yet it remains challenging due to chaotic atmospher…
cs.LG2025
Unlocking the Power of LSTM for Long Term Time Series Forecasting
Yaxuan Kong, Zepu Wang, Yuqi Nie +5
Traditional recurrent neural network architectures, such as long short-term memory neural networks (LSTM), have historically held a prominent role in time series forecasting (TSF)…