A linear basis-function model computes physics residuals analytically, giving closed-form solutions to linear forward and inverse problems; on Japanese GNSS data, smoothness regularization beats elastic regularization by Bayesian model comparison.
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Physics-Informed Linear Model (PILM): Analytical Representations and Application to Crustal Strain Rate Estimation
A linear basis-function model computes physics residuals analytically, giving closed-form solutions to linear forward and inverse problems; on Japanese GNSS data, smoothness regularization beats elastic regularization by Bayesian model comparison.