Operator Learning: A Survey

License: arXiv preprint (copyright held by authors) · Updated 2026-02-18

The survey unifies the operator-learning landscape: problem formulation on function spaces, universal approximation results, the main architecture families, and practical guidance on sampling, discretization and generalization.

Reading order: Skim the formulation chapters first, then dive into the architecture comparison section to pick a starting point for your own problem.

Tags: Operator LearningSurveyDeepONetFNOTheory
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