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Figure 4
I(Q) generated using a separate set of parameters, (a) σk, (b) α and (c) Γ, which were not included in the training dataset, to evaluate the accuracy of the KAN-based inversion algorithm. Panels (d)–(f) display the ratio between KAN-produced curves and the test set. The comparison reveals excellent quantitative agreement between the I(Q) values obtained from GLW (colored open symbols) and those generated by KAN (solid curves) across the examined parameter ranges. This agreement underscores the numerical precision and robustness of the KAN-based regression method.

Journal logoJOURNAL OF
APPLIED
CRYSTALLOGRAPHY
ISSN: 1600-5767
Volume 58| Part 2| April 2025|
https://doi.org/10.1107/S1600576725000317
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