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

A Deep Prior Approach to Magnetic Particle Imaging. - Sören Dittmer; Tobias Kluth; Daniel Otero Baguer; Peter Maass (MLMIR@MICCAI, 2020)

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

Regularization by Architecture: A Deep Prior Approach for Inverse Problems. - Sören Dittmer; Tobias Kluth; Peter Maass; Daniel Otero Baguer (J. Math. Imaging Vis., 2020)

Deeply supervised UNet for semantic segmentation to assist dermatopathological assessment of Basal Cell Carcinoma (BCC). - Jean Le'Clerc Arrastia; Nick Heilenkötter; Daniel Otero Baguer; Lena Hauberg-Lotte; Tobias Boskamp; Sonja Hetzer; Nicole Duschner; Jörg Schaller; Peter Maaß (CoRR, 2021)

Deeply Supervised UNet for Semantic Segmentation to Assist Dermatopathological Assessment of Basal Cell Carcinoma. - Jean Le'Clerc Arrastia; Nick Heilenkötter; Daniel Otero Baguer; Lena Hauberg-Lotte; Tobias Boskamp; Sonja Hetzer; Nicole Duschner; Jörg Schaller; Peter Maass (J. Imaging, 2021)

StainCUT: Stain Normalization with Contrastive Learning. - José Carlos Gutiérrez Menéndez; Daniel Otero Baguer; Peter Maass (J. Imaging, 2022)

How GAN Generators can Invert Networks in Real-Time. - Rudolf Herdt; Maximilian Schmidt; Daniel Otero Baguer; Jean Le'Clerc Arrastia; Peter Maaß (ACML, 2023)

Model Stitching and Visualization How GAN Generators can Invert Networks in Real-Time. - Rudolf Herdt; Maximilian Schmidt; Daniel Otero Baguer; Jean Le'Clerc Arrastia; Peter Maass (CoRR, 2023)

Smooth Deep Saliency. - Rudolf Herdt; Maximilian Schmidt; Daniel Otero Baguer; Peter Maaß (CoRR, 2024)

Concept Based Explanations and Class Contrasting. - Rudolf Herdt; Daniel Otero Baguer (CoRR, 2025)