Johannes Leuschner

18 papers Journal 16Unranked 1

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	Image Reconstruction via Deep Image Prior Subspaces. Trans. Mach. Learn. Res. Riccardo Barbano, Javier Antorán, Johannes Leuschner, José Miguel Hernández-Lobato, Bangti Jin, Zeljko Kereta
2024	J	`jnl`	Learning-Based Approaches for Reconstructions With Inexact Operators in nanoCT Applications. IEEE Trans. Computational Imaging Tom Lütjen, Fabian Schönfeld, Alice Oberacker, Johannes Leuschner, Maximilian Schmidt, Anne Wald, Tobias Kluth
2023	—	`—`	Deep learning for computed tomography reconstruction - learned methods, deep image prior and uncertainty estimation Johannes Leuschner
2023	J	`jnl`	Fast and Painless Image Reconstruction in Deep Image Prior Subspaces. CoRR Riccardo Barbano, Javier Antorán, Johannes Leuschner, José Miguel Hernández-Lobato, Zeljko Kereta, Bangti Jin
2023	J	`jnl`	Learning-based approaches for reconstructions with inexact operators in nanoCT applications. CoRR Tom Lütjen, Fabian Schönfeld, Alice Oberacker, Johannes Leuschner, Maximilian Schmidt, Anne Wald, Tobias Kluth
2023	—	`conf`	SVD-DIP: Overcoming the Overfitting Problem in DIP-based CT Reconstruction. MIDL Marco Nittscher, Michael Falk Lameter, Riccardo Barbano, Johannes Leuschner, Bangti Jin, Peter Maass
2023	J	`jnl`	SVD-DIP: Overcoming the Overfitting Problem in DIP-based CT Reconstruction. CoRR Marco Nittscher, Michael Lameter, Riccardo Barbano, Johannes Leuschner, Bangti Jin, Peter Maass
2023	J	`jnl`	Uncertainty Estimation for Computed Tomography with a Linearised Deep Image Prior. Trans. Mach. Learn. Res. Javier Antorán, Riccardo Barbano, Johannes Leuschner, José Miguel Hernández-Lobato, Bangti Jin
2022	J	`jnl`	A Probabilistic Deep Image Prior for Computational Tomography. CoRR Javier Antorán, Riccardo Barbano, Johannes Leuschner, José Miguel Hernández-Lobato, Bangti Jin
2022	J	`jnl`	An Educated Warm Start for Deep Image Prior-Based Micro CT Reconstruction. IEEE Trans. Computational Imaging Riccardo Barbano, Johannes Leuschner, Maximilian Schmidt, Alexander Denker, Andreas Hauptmann, Peter Maass, Bangti Jin
2022	J	`jnl`	Bayesian Experimental Design for Computed Tomography with the Linearised Deep Image Prior. CoRR Riccardo Barbano, Johannes Leuschner, Javier Antorán, Bangti Jin, José Miguel Hernández-Lobato
2021	J	`jnl`	Conditional Invertible Neural Networks for Medical Imaging. J. Imaging Alexander Denker, Maximilian Schmidt, Johannes Leuschner, Peter Maass
2021	J	`jnl`	Is Deep Image Prior in Need of a Good Education? CoRR Riccardo Barbano, Johannes Leuschner, Maximilian Schmidt, Alexander Denker, Andreas Hauptmann, Peter Maaß, Bangti Jin
2021	J	`jnl`	Quantitative Comparison of Deep Learning-Based Image Reconstruction Methods for Low-Dose and Sparse-Angle CT Applications. J. Imaging 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
2021	J	`jnl`	Training a Deep Neural Network via Policy Gradients for Blind Source Separation in Polyphonic Music Recordings. CoRR Sören Schulze, Johannes Leuschner, Emily J. King
2020	J	`jnl`	Computed Tomography Reconstruction Using Deep Image Prior and Learned Reconstruction Methods. CoRR Daniel Otero Baguer, Johannes Leuschner, Maximilian Schmidt
2019	J	`jnl`	Supervised non-negative matrix factorization methods for MALDI imaging applications. Bioinform. Johannes Leuschner, Maximilian Schmidt, Pascal Fernsel, Delf Lachmund, Tobias Boskamp, Peter Maass
2019	J	`jnl`	The LoDoPaB-CT Dataset: A Benchmark Dataset for Low-Dose CT Reconstruction Methods. CoRR Johannes Leuschner, Maximilian Schmidt, Daniel Otero Baguer, Peter Maaß