AINeutralarXiv – CS AI · 6h ago6/10
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Structure-Preserving Learning Improves Geometry Generalization in Neural PDEs
Researchers introduce Geo-NeW, a neural network method that solves Partial Differential Equations while preserving physical laws and generalizing to unseen geometries. The approach combines learned differential operators with finite element spaces that explicitly encode geometry information, achieving state-of-the-art performance on PDE benchmarks with significant improvements on out-of-distribution test cases.