  The analytic deep prior (ADP) approach was recently introduced for the
theoretical analysis of deep image prior (DIP) methods with special network
architectures. In this paper, we prove that ADP is in fact equivalent to
classical variational Ivanov methods for solving ill-posed inverse problems.
Besides, we propose a new variant which incorporates the strategy of early
stopping into the ADP model. For both variants, we show how classical
regularization properties (existence, stability, convergence) can be obtained
under common assumptions.
