In practice, the MTE undergoes the training of a multitude of models with diverse architectures and then employs a rigorous selection process to identify and retain the most effective models for further optimization for the predictive task at hand. For both TPE and MP we use the optuna implementation optuna. Full ranges for the model parameters during hyper-parameter optimization can be found in Supplementary information 1.