Introduction to inversion theory
Elements of probability theory
Vector spaces of models and data
Principles of regularization theory
Linear inverse problems
Probabilistic methods of inverse problem solution
Gradient-type methods of non-linear inversion
Joint inversion based on analytical and statistical relationships between different physical properties
Joint inversion based on structural similarities
Joint focusing inversion of multiphysics data
Joint minimum entropy inversion
Gramian method of generalized joint inversion
Probabilistic approach to gramian inversion
Simultaneous processing and fusion of multiphysics data and images
Machine learning in the context of inversion theory
Machine learning inversion of multiphysics data
Modeling and inversion of potential field data
Case histories of joint inversion of gravity and magnetic data. .