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Abstract:
In this talk I will give a basic introduction to inverse problems, highlighting commonalities and differences between deterministic and statistical ones, specific difficulties, and important examples. Two
major topics will be covered: regularization (i.e. the construction of suitable estimators from noisy data) and inference (i.e. statistically rigorous statements about properties of the unknown quantity of interest
based on noisy data).
For both topics, I will explain a general approach to design and analyze corresponding methods, and I will also discuss applications e.g. from medical imaging and super-resolution microscopy.