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cs.LG2026
Geometry-physics confounding impairs PDE learning across varying domains
Yinghao Cheng, Gengxiang Chen, Xu Liu +6
Learning partial differential equation (PDE) dynamics across varying domains is central to predictive modelling and data-driven discovery of governing equations. However, geometric…
cs.LG2026
Shape-morphing programming of soft materials on complex geometries via neural operator
Lu Chen, Gengxiang Chen, Xu Liu +4
Shape-morphing soft materials can enable diverse target morphologies through voxel-level material distribution design, offering significant potential for various applications. Desp…
cs.LG2024★ 1 cited
A general reduced-order neural operator for spatio-temporal predictive learning on complex spatial domains
Qinglu Meng, Yingguang Li, Zhiliang Deng +5
Predictive learning for spatio-temporal processes (PL-STP) on complex spatial domains plays a critical role in various scientific and engineering fields, with its essence being the…