135 citations · 214 across the 16 of their papers we have counts for
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cs.LG2026
Inferring physical fields in coupled systems with unknown parameters from incomplete observations using physics-constrained attentive neural operators
Shilun Wei, Xiaoqiang Sun, Wei Li +1
Given incomplete measurements of a single physical field in a coupled system with unknown parameters, can we infer its full physical state and identify the underlying parameters? T…
cs.LG2026
Deep Adaptive Dimension Reduction for Bayesian Inference in Inverse Problems
Yueyang Wang, Xili Wang, Kejun Tang +3
Solving high-dimensional PDE-governed inverse problems is often challenging due to complex non-Gaussian posterior distributions, expensive forward model evaluations, and misspecifi…
cs.LG2019★ 135 cited
D3M: A deep domain decomposition method for partial differential equations
Ke Li, Kejun Tang, Tianfan Wu +1
A state-of-the-art deep domain decomposition method (D3M) based on the variational principle is proposed for partial differential equations (PDEs). The solution of PDEs can be form…