2 papers
cs.LG2025
From Cheap Geometry to Expensive Physics: Elevating Neural Operators via Latent Shape Pretraining
Zhizhou Zhang, Youjia Wu, Kaixuan Zhang +1
Industrial design evaluation often relies on high-fidelity simulations of governing partial differential equations (PDEs). While accurate, these simulations are computationally exp…
cs.LG2025
Operator Learning with Domain Decomposition for Geometry Generalization in PDE Solving
Jianing Huang, Kaixuan Zhang, Youjia Wu +1
Neural operators have become increasingly popular in solving \textit{partial differential equations} (PDEs) due to their superior capability to capture intricate mappings between f…