Regularization Theory of the Analytic Deep Prior Approach. - Clemens Arndt (CoRR, 2022)

Invertible residual networks in the context of regularization theory for linear inverse problems. - Clemens Arndt; Alexander Denker; Sören Dittmer; Nick Heilenkötter; Meira Iske; Tobias Kluth; Peter Maass; Judith Nickel (CoRR, 2023)

Bayesian view on the training of invertible residual networks for solving linear inverse problems. - Clemens Arndt; Sören Dittmer; Nick Heilenkötter; Meira Iske; Tobias Kluth; Judith Nickel (CoRR, 2023)

Invertible ResNets for Inverse Imaging Problems: Competitive Performance with Provable Regularization Properties. - Clemens Arndt; Judith Nickel (CoRR, 2024)