Feb. 13, 2024, 5:45 a.m. | Rui Zhang Qi Meng Zhi-Ming Ma

cs.LG updates on arXiv.org arxiv.org

Neural operators have been explored as surrogate models for simulating physical systems to overcome the limitations of traditional partial differential equation (PDE) solvers. However, most existing operator learning methods assume that the data originate from a single physical mechanism, limiting their applicability and performance in more realistic scenarios. To this end, we propose Physical Invariant Attention Neural Operator (PIANO) to decipher and integrate the physical invariants (PI) for operator learning from the PDE series with various physical mechanisms. PIANO employs …

cs.lg cs.na math.na physics.comp-ph

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