Key hyperparameters in our study include the batch size (set to 2000), the number of IPs (set to 5000 in the final configuration), the learning rate (1 × 10⁻³), and the maximum number of training epochs (200), with early stopping configured to trigger after 5 epochs without significant improvement (minimum delta of 1 × 10⁻⁴). In addition, the model learns the GP kernel hyperparameters, specifically, a length scale and a noise term while using the combined kernel.