Hypernetwork-Parameterized Spatially Adaptive Neural Operators for PDE Learning
Spatially heterogeneous partial differential equations (PDEs) exhibit location-dependent dynamics arising from variations in geometry and physical coefficients. Existing neural operators improve localized modeling through multiscale features, attention mechanisms, or domain decomposition, yet their update rules often r...
Jia-Quan Zhang, Chaoning Zhang, Shuxu Chen et al.
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