4 citations · 5 across the 4 of their papers we have counts for
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cs.LG2024★ 1 cited
State-observation augmented diffusion model for nonlinear assimilation with unknown dynamics
Zhuoyuan Li, Bin Dong, Pingwen Zhang
Data assimilation has become a key technique for combining physical models with observational data to estimate state variables. However, classical assimilation algorithms often str…
cs.LG2023★ 4 cited
Latent assimilation with implicit neural representations for unknown dynamics
Zhuoyuan Li, Bin Dong, Pingwen Zhang
Data assimilation is crucial in a wide range of applications, but it often faces challenges such as high computational costs due to data dimensionality and incomplete understanding…
cs.LG2023
Learning to simulate partially known spatio-temporal dynamics with trainable difference operators
Xiang Huang, Zhuoyuan Li, Hongsheng Liu +4
Recently, using neural networks to simulate spatio-temporal dynamics has received a lot of attention. However, most existing methods adopt pure data-driven black-box models, which…