view article
Figure 3
The KAN architecture models the relationship between scattering parameters σk, Γ, α and the resulting scattering intensity I(Q) as a function of the wave vector Q. KAN 1 maps the scattering parameters into a higher-dimensional space using three layers (3, 7 and 3 neurons) to capture nonlinear dependencies. KAN 2 integrates Q with the KAN 1 outputs, using layers with 9, 1 and 1 neuron to predict [I(Q;\sigma_{k},\Gamma,\alpha)], aligning with experimental data to reveal lamellar phase structures.

Journal logoJOURNAL OF
APPLIED
CRYSTALLOGRAPHY
ISSN: 1600-5767
Volume 58| Part 2| April 2025|
https://doi.org/10.1107/S1600576725000317
Follow J. Appl. Cryst.
Sign up for e-alerts
E-alerts
Follow J. Appl. Cryst. on Twitter
Twitter
Follow us on facebook
Facebook
Sign up for RSS feeds
RSS