22 citations · 45 across the 12 of their papers we have counts for
3 papers · 2 filters
MillGNN: Learning Multi-Scale Lead-Lag Dependencies for Multi-Variate Time Series Forecasting
Binqing Wu, Zongjiang Shang, Jianlong Huang +1
Multi-variate time series (MTS) forecasting is crucial for various applications. Existing methods have shown promising results owing to their strong ability to capture intra- and i…
ST-Hyper: Learning High-Order Dependencies Across Multiple Spatial-Temporal Scales for Multivariate Time Series Forecasting
Binqing Wu, Jianlong Huang, Zongjiang Shang +1
In multivariate time series (MTS) forecasting, many deep learning based methods have been proposed for modeling dependencies at multiple spatial (inter-variate) or temporal (intra-…
Physics-Guided Learning of Meteorological Dynamics for Weather Downscaling and Forecasting
Yingtao Luo, Shikai Fang, Binqing Wu +2
Weather forecasting is essential but remains computationally intensive and physically incomplete in traditional numerical weather prediction (NWP) methods. Deep learning (DL) model…