Johannes Leuschner

Orcid: 0000-0001-7361-9523

According to our database1, Johannes Leuschner authored at least 16 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Image Reconstruction via Deep Image Prior Subspaces.
Trans. Mach. Learn. Res., 2024

Learning-Based Approaches for Reconstructions With Inexact Operators in nanoCT Applications.
IEEE Trans. Computational Imaging, 2024

2023
Deep learning for computed tomography reconstruction - learned methods, deep image prior and uncertainty estimation
PhD thesis, 2023

Uncertainty Estimation for Computed Tomography with a Linearised Deep Image Prior.
Trans. Mach. Learn. Res., 2023

Fast and Painless Image Reconstruction in Deep Image Prior Subspaces.
CoRR, 2023

SVD-DIP: Overcoming the Overfitting Problem in DIP-based CT Reconstruction.
Proceedings of the Medical Imaging with Deep Learning, 2023

2022
An Educated Warm Start for Deep Image Prior-Based Micro CT Reconstruction.
IEEE Trans. Computational Imaging, 2022

Bayesian Experimental Design for Computed Tomography with the Linearised Deep Image Prior.
CoRR, 2022

A Probabilistic Deep Image Prior for Computational Tomography.
CoRR, 2022

2021
Quantitative Comparison of Deep Learning-Based Image Reconstruction Methods for Low-Dose and Sparse-Angle CT Applications.
J. Imaging, 2021

Conditional Invertible Neural Networks for Medical Imaging.
J. Imaging, 2021

Is Deep Image Prior in Need of a Good Education?
CoRR, 2021

Training a Deep Neural Network via Policy Gradients for Blind Source Separation in Polyphonic Music Recordings.
CoRR, 2021

2020
Computed Tomography Reconstruction Using Deep Image Prior and Learned Reconstruction Methods.
CoRR, 2020

2019
The LoDoPaB-CT Dataset: A Benchmark Dataset for Low-Dose CT Reconstruction Methods.
CoRR, 2019

Supervised non-negative matrix factorization methods for MALDI imaging applications.
Bioinform., 2019


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