1 citations · 1 across the 12 of their papers we have counts for
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SeesawNet: Towards Non-stationary Time Series Forecasting with Balanced Modeling of Common and Specific Dependencies
Hao Li, Lu Zhang, Liu Chong +3
Instance normalization (IN) is widely used in non-stationary multivariate time series forecasting to reduce distribution shifts and highlight common patterns across samples. Howeve…
FuXiWeather2: Learning accurate atmospheric state estimation for operational global weather forecasting
Xiaoze Xu, Xiuyu Sun, Songling Zhu +5
Numerical weather prediction has long been constrained by the computational bottlenecks inherent in data assimilation and numerical modeling. While machine learning has accelerated…
AviaSafe: A Physics-Informed Data-Driven Model for Aviation Safety-Critical Cloud Forecasts
Zijian Zhu, Qiusheng Huang, Anboyu Guo +2
Current AI weather forecasting models predict conventional atmospheric variables but cannot distinguish between cloud microphysical species critical for aviation safety. We introdu…
Revealing the Potential of Learnable Perturbation Ensemble Forecast Model for Tropical Cyclone Prediction
Jun Liu, Tao Zhou, Jiarui Li +5
Tropical cyclones (TCs) are highly destructive and inherently uncertain weather systems. Ensemble forecasting helps quantify these uncertainties, yet traditional systems are constr…
FuXi-Ocean: A Global Ocean Forecasting System with Sub-Daily Resolution
Qiusheng Huang, Yuan Niu, Xiaohui Zhong +5
Accurate, high-resolution ocean forecasting is crucial for maritime operations and environmental monitoring. While traditional numerical models are capable of producing sub-daily,…
A machine learning model for skillful climate system prediction
Chenguang Zhou, Lei Chen, Xiaohui Zhong +8
Climate system models (CSMs), through integrating cross-sphere interactions among the atmosphere, ocean, land, and cryosphere, have emerged as pivotal tools for deciphering climate…