Inverting Gradients - How easy is it to break privacy in federated learning? - Jonas Geiping; Hartmut Bauermeister; Hannah Dröge; Michael Moeller 001 (NeurIPS, 2020)

Learning or Modelling? An Analysis of Single Image Segmentation Based on Scribble Information. - Hannah Dröge; Michael Möller 001 (ICIP, 2021)

Mitral Valve Segmentation Using Robust Nonnegative Matrix Factorization. - Hannah Dröge; Baichuan Yuan; Rafael Llerena; Jesse T. Yen; Michael Möller 001; Andrea L. Bertozzi (J. Imaging, 2021)

Explorable Data Consistent CT Reconstruction. - Hannah Dröge; Yuval Bahat; Felix Heide; Michael Moeller 001 (BMVC, 2022)

Non-Smooth Energy Dissipating Networks. - Hannah Dröge; Thomas Möllenhoff; Michael Möller 001 (ICIP, 2022)

Evaluating Adversarial Robustness of Low dose CT Recovery. - Kanchana Vaishnavi Gandikota; Paramanand Chandramouli; Hannah Dröge; Michael Möller 001 (MIDL, 2023)

Kissing to Find a Match: Efficient Low-Rank Permutation Representation. - Hannah Dröge; Zorah Lähner; Yuval Bahat; Onofre Martorell Nadal; Felix Heide; Michael Moeller 001 (NeurIPS, 2023)

Kissing to Find a Match: Efficient Low-Rank Permutation Representation. - Hannah Dröge; Zorah Lähner; Yuval Bahat; Onofre Martorell; Felix Heide; Michael Möller 001 (CoRR, 2023)

Robustness and Exploration of Variational and Machine Learning Approaches to Inverse Problems: An Overview. - Alexander Auras; Kanchana Vaishnavi Gandikota; Hannah Dröge; Michael Moeller 001 (CoRR, 2024)

On the confluence of machine learning and model-based energy minimization methods for computer vision. - Hannah Dröge (2024)

VHS: High-Resolution Iterative Stereo Matching with Visual Hull Priors. - Markus Plack; Hannah Dröge; Leif Van Holland; Matthias B. Hullin (WACV, 2025)

Capture Stage Environments: A Guide to Better Matting. - Hannah Dröge; Janelle Pfeifer; Saskia Rabich; Markus Plack; Reinhard Klein; Matthias B. Hullin (CoRR, 2025)