Fabian Altekrüger

According to our database, Fabian Altekrüger authored at least 11 papers between 2022 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Stability of Data-Dependent Ridge-Regularization for Inverse Problems.

Sebastian Neumayer, Fabian Altekrüger

CoRR, 2024

Generative Sliced MMD Flows with Riesz Kernels.

Johannes Hertrich, Christian Wald, Fabian Altekrüger, Paul Hagemann

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Posterior Sampling Based on Gradient Flows of the MMD with Negative Distance Kernel.

Paul Hagemann, Johannes Hertrich, Fabian Altekrüger, Robert Beinert, Jannis Chemseddine, Gabriele Steidl

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Learning Regularization Parameter-Maps for Variational Image Reconstruction Using Deep Neural Networks and Algorithm Unrolling.

Andreas Kofler, Fabian Altekrüger, Fatima Antarou Ba, Christoph Kolbitsch, Evangelos Papoutsellis, David Schote, Clemens Sirotenko, Felix Frederik Zimmermann, Kostas Papafitsoros

SIAM J. Imaging Sci., December, 2023

WPPNets and WPPFlows: The Power of Wasserstein Patch Priors for Superresolution.

Fabian Altekrüger, Johannes Hertrich

SIAM J. Imaging Sci., September, 2023

Conditional Generative Models are Provably Robust: Pointwise Guarantees for Bayesian Inverse Problems.

Fabian Altekrüger, Paul Hagemann, Gabriele Steidl

Trans. Mach. Learn. Res., 2023

Learning from small data sets: Patch-based regularizers in inverse problems for image reconstruction.

Moritz Piening, Fabian Altekrüger, Johannes Hertrich, Paul Hagemann, Andrea Walther, Gabriele Steidl

CoRR, 2023

Neural Wasserstein Gradient Flows for Maximum Mean Discrepancies with Riesz Kernels.

Fabian Altekrüger, Johannes Hertrich, Gabriele Steidl

CoRR, 2023

Neural Wasserstein Gradient Flows for Discrepancies with Riesz Kernels.

Fabian Altekrüger, Johannes Hertrich, Gabriele Steidl

Proceedings of the International Conference on Machine Learning, 2023

2022

PatchNR: Learning from Small Data by Patch Normalizing Flow Regularization.

Fabian Altekrüger, Alexander Denker, Paul Hagemann, Johannes Hertrich, Peter Maass, Gabriele Steidl

CoRR, 2022

WPPNets: Unsupervised CNN Training with Wasserstein Patch Priors for Image Superresolution.

Fabian Altekrüger, Johannes Hertrich

CoRR, 2022