Equation Recast for Canonical Operator Learning Across Parametric PDEs
Learning solution operators across broad parameter ranges can require substantial coverage of both input functions and physical parameters, particularly for purely data-driven parametric models. In addition, the resulting models may fail silently outside the training distribution. We introduce equation recast, which re...
Qi-Yun Cheng, Valentin Duruisseaux, C. Clauser et al.
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