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Equation Recast for Canonical Operator Learning Across Parametric PDEs

This story is from 2026-09-04. It is preserved in the archive; the latest stories are on the live feed.

arXiv:2609.02982v1 Announce Type: new Abstract: 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 outs…

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  1. 2026-09-04 04:00 · arXiv cs.LG
    Equation Recast for Canonical Operator Learning Across Parametric PDEs

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