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cs.LG2025
Efficient High-Accuracy PDEs Solver with the Linear Attention Neural Operator
Ming Zhong, Zhenya Yan
Neural operators offer a powerful data-driven framework for learning mappings between function spaces, in which the transformer-based neural operator architecture faces a fundament…
cs.LG2025
PMNO: A novel physics guided multi-step neural operator predictor for partial differential equations
Jin Song, Kenji Kawaguchi, Zhenya Yan
Neural operators, which aim to approximate mappings between infinite-dimensional function spaces, have been widely applied in the simulation and prediction of physical systems. How…