Supervised non-negative matrix factorization methods for MALDI imaging applications. - Johannes Leuschner; Maximilian Schmidt; Pascal Fernsel; Delf Lachmund; Tobias Boskamp; Peter Maass (Bioinform., 2019)

The LoDoPaB-CT Dataset: A Benchmark Dataset for Low-Dose CT Reconstruction Methods. - Johannes Leuschner; Maximilian Schmidt; Daniel Otero Baguer; Peter Maaß (CoRR, 2019)

Computed Tomography Reconstruction Using Deep Image Prior and Learned Reconstruction Methods. - Daniel Otero Baguer; Johannes Leuschner; Maximilian Schmidt (CoRR, 2020)

Training a Deep Neural Network via Policy Gradients for Blind Source Separation in Polyphonic Music Recordings. - Sören Schulze; Johannes Leuschner; Emily J. King (CoRR, 2021)

Is Deep Image Prior in Need of a Good Education? - Riccardo Barbano; Johannes Leuschner; Maximilian Schmidt; Alexander Denker; Andreas Hauptmann; Peter Maaß; Bangti Jin (CoRR, 2021)

Conditional Invertible Neural Networks for Medical Imaging. - Alexander Denker; Maximilian Schmidt; Johannes Leuschner; Peter Maass (J. Imaging, 2021)

Quantitative Comparison of Deep Learning-Based Image Reconstruction Methods for Low-Dose and Sparse-Angle CT Applications. - Johannes Leuschner; Maximilian Schmidt; Poulami Somanya Ganguly; Vladyslav Andriiashen; Sophia Bethany Coban; Alexander Denker; Dominik F. Bauer; Amir Hadjifaradji; Kees Joost Batenburg; Peter Maass; Maureen van Eijnatten (J. Imaging, 2021)

A Probabilistic Deep Image Prior for Computational Tomography. - Javier Antorán; Riccardo Barbano; Johannes Leuschner; José Miguel Hernández-Lobato; Bangti Jin (CoRR, 2022)

Bayesian Experimental Design for Computed Tomography with the Linearised Deep Image Prior. - Riccardo Barbano; Johannes Leuschner; Javier Antorán; Bangti Jin; José Miguel Hernández-Lobato (CoRR, 2022)

An Educated Warm Start for Deep Image Prior-Based Micro CT Reconstruction. - Riccardo Barbano; Johannes Leuschner; Maximilian Schmidt; Alexander Denker; Andreas Hauptmann; Peter Maass; Bangti Jin (IEEE Trans. Computational Imaging, 2022)

SVD-DIP: Overcoming the Overfitting Problem in DIP-based CT Reconstruction. - Marco Nittscher; Michael Falk Lameter; Riccardo Barbano; Johannes Leuschner; Bangti Jin; Peter Maass (MIDL, 2023)

Fast and Painless Image Reconstruction in Deep Image Prior Subspaces. - Riccardo Barbano; Javier Antorán; Johannes Leuschner; José Miguel Hernández-Lobato; Zeljko Kereta; Bangti Jin (CoRR, 2023)

Uncertainty Estimation for Computed Tomography with a Linearised Deep Image Prior. - Javier Antorán; Riccardo Barbano; Johannes Leuschner; José Miguel Hernández-Lobato; Bangti Jin (Trans. Mach. Learn. Res., 2023)

Deep learning for computed tomography reconstruction - learned methods, deep image prior and uncertainty estimation - Johannes Leuschner (2023)

Learning-Based Approaches for Reconstructions With Inexact Operators in nanoCT Applications. - Tom Lütjen; Fabian Schönfeld; Alice Oberacker; Johannes Leuschner; Maximilian Schmidt; Anne Wald; Tobias Kluth (IEEE Trans. Computational Imaging, 2024)

Image Reconstruction via Deep Image Prior Subspaces. - Riccardo Barbano; Javier Antorán; Johannes Leuschner; José Miguel Hernández-Lobato; Bangti Jin; Zeljko Kereta (Trans. Mach. Learn. Res., 2024)