Fig. 14From: Sensitivity-guided iterative parameter identification and data generation with BayesFlow and PELS-VAE for model calibrationParameter inference results of one test and 399 validation samples in 5 groups. In terms of the regression accuracy between the estimate and the ground truth of the model parameters, root mean squared error (RMSE), normalized root mean squared error (NRMSE) and coefficient of determination (\(R^2\)) are standard metrics. \(NRMSE =\frac{\sqrt{\frac{1}{M}\sum _{m=1}^M (\theta ^{(m)} - {\widehat{\theta }}^{(m)})^2}}{\theta _{max}-\theta _{min}}\), \(R^2 = 1 - \sum _{m=1}^{M}\frac{(\theta ^{(m)}-{\widehat{\theta }}^{(m)})^2}{(\theta ^{(m)}-{\overline{\theta }})^2}\)Back to article page