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cs.LG2024★ 6 cited
Harnessing Scale and Physics: A Multi-Graph Neural Operator Framework for PDEs on Arbitrary Geometries
Zhihao Li, Haoze Song, Di Xiao +2
Partial Differential Equations (PDEs) underpin many scientific phenomena, yet traditional computational approaches often struggle with complex, nonlinear systems and irregular geom…
cs.CE2024
Parameter estimation of structural dynamics with neural operators enabled surrogate modeling
Mingyuan Zhou, Haoze Song, Wenjing Ye +2
Parameter estimation in structural dynamics generally involves inferring the values of physical, geometric, or even customized parameters based on first principles or expert knowle…
cs.LG2024
M2NO: An Efficient Multi-Resolution Operator Framework for Dynamic Multi-Scale PDE Solvers
Zhihao Li, Zhilu Lai, Xiaobo Zhang +1
Solving high-dimensional partial differential equations (PDEs) efficiently requires handling multi-scale features across varying resolutions. To address this challenge, we present…