In such scenarios, traditional methods such as linear regression and Markov Chain Monte Carlo (MCMC) might not efficiently or accurately infer model parameters and can be computationally intensive. An example of inverse modelling of diffusion coefficients is given by . In their study, experiments are conducted to determine the diffusion coefficient of selected anions and cations through compacted clay porous media. Once the experiment is terminated, the sample is cut into slices and the amounts of ions retained in each slice is measured in order to produce the concentration profiles.