most citedReference Neural Operators: Learning the Smooth Dependence of Solutions of PDEs on Geometric Deformations

1 citations · 1 across the 2 of their papers we have counts for

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2 papers

cs.LG2025

Accelerating PDE-Constrained Optimization by the Derivative of Neural Operators

Ze Cheng, Zhuoyu Li, Xiaoqiang Wang +4

PDE-Constrained Optimization (PDECO) problems can be accelerated significantly by employing gradient-based methods with surrogate models like neural operators compared to tradition…

cs.LG2024★ 1 cited

Reference Neural Operators: Learning the Smooth Dependence of Solutions of PDEs on Geometric Deformations

Ze Cheng, Zhongkai Hao, Xiaoqiang Wang +6

For partial differential equations on domains of arbitrary shapes, existing works of neural operators attempt to learn a mapping from geometries to solutions. It often requires a l…