14 citations · 27 across the 4 of their papers we have counts for
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cs.LG2021
ST-PCNN: Spatio-Temporal Physics-Coupled Neural Networks for Dynamics Forecasting
Yu Huang, James Li, Min Shi +5
Ocean current, fluid mechanics, and many other spatio-temporal physical dynamical systems are essential components of the universe. One key characteristic of such systems is that c…
cs.LG2021
Physics-Coupled Spatio-Temporal Active Learning for Dynamical Systems
Yu Huang, Yufei Tang, Xingquan Zhu +4
Spatio-temporal forecasting is of great importance in a wide range of dynamical systems applications from atmospheric science, to recent COVID-19 spread modeling. These application…
cs.LG2020★ 13 cited
Physics-informed Tensor-train ConvLSTM for Volumetric Velocity Forecasting of Loop Current
Yu Huang, Yufei Tang, Hanqi Zhuang +2
According to the National Academies, a weekly forecast of velocity, vertical structure, and duration of the Loop Current (LC) and its eddies is critical for understanding the ocean…