An explicit budget allocation condition is derived for two-stage kernel-based operator learning, relating training set size, input observations, and output resolution, alongside a physics-informed online reconstruction extension.
Kernel methods are competitive for operator learning
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Kernel-based Operator Learning: Error Analysis, Budget Allocation, and a Physics-Informed Extension
An explicit budget allocation condition is derived for two-stage kernel-based operator learning, relating training set size, input observations, and output resolution, alongside a physics-informed online reconstruction extension.