Generalization error bounds for Picard-type operator learning in nonlinear parabolic PDEs separate implementation error from estimation error, showing that greater Picard depth reduces truncation error without unbounded growth in entropy-based estimation error.
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Generalization Error Bounds for Picard-Type Operator Learning in Nonlinear Parabolic PDEs
Generalization error bounds for Picard-type operator learning in nonlinear parabolic PDEs separate implementation error from estimation error, showing that greater Picard depth reduces truncation error without unbounded growth in entropy-based estimation error.