ReAl: Refine neural operators via aligning dynamical flow
Neural partial differential equation (PDE) surrogates trained with mean squared error (MSE) can capture dominant dynamics but often lose high-frequency information and fine-scale structures. Generative models (e.g., Flow Matching) can capture the distribution of fine-scale details, yet stochastic errors may accumulate...
Jing Xu, Zeng-Lin Xu, Li Yi et al.
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