The research field of Inverse Problems has witnessed a tremendous growth in recent years, due to its ability to capture and tackle complex problems occuring in real-world applications. However, numerous inverse problems are ill-posed.

Depending on the nature of the problem, various approaches can be considered for stable approximation of the solution. This talk discusses variational and iterative regularization approaches, with emphasis on reconstructing nonnegative solutions when nonnegative data are available.