Personalized visual aesthetics. - Edward A. Vessel; Jonathan Stahl; Natalia Maurer; Alexander Denker; G. Gabrielle Starr (Human Vision and Electronic Imaging, 2014)

Feature reduction for machine learning on molecular features: The GeneScore. - Alexander Denker; Anastasia Steshina; Theresa Grooss; Frank Ueckert; Sylvia Nürnberg (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)

PatchNR: Learning from Small Data by Patch Normalizing Flow Regularization. - Fabian Altekrüger; Alexander Denker; Paul Hagemann; Johannes Hertrich; Peter Maass; Gabriele Steidl (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)

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)

Score-Based Generative Models for PET Image Reconstruction. - Imraj RD Singh; Alexander Denker; Riccardo Barbano; Zeljko Kereta; Bangti Jin; Kris Thielemans; Peter Maass; Simon R. Arridge (CoRR, 2023)

Steerable Conditional Diffusion for Out-of-Distribution Adaptation in Imaging Inverse Problems. - Riccardo Barbano; Alexander Denker; Hyungjin Chung; Tae-Hoon Roh; Simon Arrdige; Peter Maass; Bangti Jin; Jong Chul Ye (CoRR, 2023)

Convergence Properties of Score-Based Models for Linear Inverse Problems Using Graduated Optimisation. - Pascal Fernsel; Zeljko Kereta; Alexander Denker (MLSP, 2024)

DEFT: Efficient Fine-tuning of Diffusion Models by Learning the Generalised $h$-transform. - Alexander Denker; Francisco Vargas 001; Shreyas Padhy; Kieran Didi; Simon V. Mathis; Riccardo Barbano; Vincent Dutordoir; Emile Mathieu; Urszula Julia Komorowska; Pietro Lió (NeurIPS, 2024)

Convergence Properties of Score-Based Models using Graduated Optimisation for Linear Inverse Problems. - Pascal Fernsel; Zeljko Kereta; Alexander Denker (CoRR, 2024)

DEFT: Efficient Finetuning of Conditional Diffusion Models by Learning the Generalised h-transform. - Alexander Denker; Francisco Vargas 001; Shreyas Padhy; Kieran Didi; Simon V. Mathis; Vincent Dutordoir; Riccardo Barbano; Emile Mathieu; Urszula Julia Komorowska; Pietro Lio (CoRR, 2024)

Data-driven approaches for electrical impedance tomography image segmentation from partial boundary data. - Alexander Denker; Zeljko Kereta; Imraj RD Singh; Tom Freudenberg; Tobias Kluth; Peter Maass; Simon R. Arridge (CoRR, 2024)

Invertible neural networks and normalizing flows for image reconstruction. - Alexander Denker (2024)

Plug-and-Play Half-Quadratic Splitting for Ptychography. - Alexander Denker; Johannes Hertrich; Zeljko Kereta; Silvia Cipiccia; Ecem Erin; Simon R. Arridge (SSVM (1), 2025)

Iterative Importance Fine-tuning of Diffusion Models. - Alexander Denker; Shreyas Padhy; Francisco Vargas 001; Johannes Hertrich (CoRR, 2025)

Steerable Conditional Diffusion for Out-of-Distribution Adaptation in Medical Image Reconstruction. - Riccardo Barbano; Alexander Denker; Hyungjin Chung; Tae-Hoon Roh; Simon R. Arridge; Peter Maass; Bangti Jin; Jong Chul Ye (IEEE Trans. Medical Imaging, 2025)