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cs.LG2026
Single-condition neural solvers encode transferable response spaces for parametric differential equations
Wenbo Cao, Weiwei Zhang
Operator learning for parametric partial differential equations (PDEs) typically builds global models over prescribed domains, requiring cross-condition data or costly physics-cons…
cs.LG2026
Linearized subspace refinement framework to expose hidden accuracy in trained neural networks
Wenbo Cao, Weiwei Zhang
Neural networks trained by gradient-based methods often exhibit optimization-induced accuracy plateaus in scientific machine learning tasks. We present Linearized Subspace Refineme…
cs.LG2023★ 7 cited
TSONN: Time-stepping-oriented neural network for solving partial differential equations
Wenbo Cao, Weiwei Zhang
Deep neural networks (DNNs), especially physics-informed neural networks (PINNs), have recently become a new popular method for solving forward and inverse problems governed by par…