AI RESEARCH
When Attention Beats Fourier: Multi-Scale Transformers for PDE Solving on Irregular Domains
arXiv CS.AI
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ArXi:2605.08318v1 Announce Type: cross We study the problem of \emph{architecture selection} for deep learning models trained to solve partial differential equations (PDEs), asking when transformer-based architectures with learned attention outperform Fourier-domain neural operators. We