The SHEMAT-Suite provides an approach for deterministic Bayesian inversion. Its specialty is that derivates are calculated by Automatic Differentiation (AD) instead of divided differences. The approach and methodology is explained in [Rath et al. (2006)](https://academic.oup.com/gji/article/167/1/453/2085661).
The SHEMAT-Suite provides an approach for deterministic Bayesian inversion for parameter estimation. Its specialty is that derivatives of the forward model, which are required for producing the Jacobian matrix, are calculated by Automatic Differentiation (AD) instead of numerical differentiation (divided differences). AD produces exact results free of any truncation error. The inverse problem is solved by a fundamental Gauss-Newton iteration scheme. The approach and methodology is explained in detail in [Rath et al. (2006)](https://academic.oup.com/gji/article/167/1/453/2085661).
