Deep learning for tumor classification in imaging mass spectrometry. - Jens Behrmann; Christian Etmann; Tobias Boskamp; Rita Casadonte; Jörg Kriegsmann; Peter Maaß (Bioinform., 2018)

On the Connection Between Adversarial Robustness and Saliency Map Interpretability. - Christian Etmann; Sebastian Lunz; Peter Maass; Carola Schönlieb (ICML, 2019)

A Closer Look at Double Backpropagation. - Christian Etmann (CoRR, 2019)

Deep Relevance Regularization: Interpretable and Robust Tumor Typing of Imaging Mass Spectrometry Data. - Christian Etmann; Maximilian Schmidt; Jens Behrmann; Tobias Boskamp; Lena Hauberg-Lotte; Annette Peter; Rita Casadonte; Jörg Kriegsmann; Peter Maass (CoRR, 2019)

iUNets: Learnable Invertible Up- and Downsampling for Large-Scale Inverse Problems. - Christian Etmann; Rihuan Ke; Carola-Bibiane Schönlieb (MLSP, 2020)

iUNets: Fully invertible U-Nets with Learnable Up- and Downsampling. - Christian Etmann; Rihuan Ke; Carola-Bibiane Schönlieb (CoRR, 2020)

Structure preserving deep learning. - Elena Celledoni; Matthias J. Ehrhardt; Christian Etmann; Robert I. McLachlan; Brynjulf Owren; Carola-Bibiane Schönlieb; Ferdia Sherry (CoRR, 2020)

Machine learning for COVID-19 detection and prognostication using chest radiographs and CT scans: a systematic methodological review. - Michael Roberts; Derek Driggs; Matthew Thorpe; Julian D. Gilbey; Michael Yeung; Stephan Ursprung; Angelica I. Avilés-Rivero; Christian Etmann; Cathal McCague; Lucian Beer; Jonathan R. Weir-McCall; Zhongzhao Teng; et al. (CoRR, 2020)

Depthwise Separable Convolutions Allow for Fast and Memory-Efficient Spectral Normalization. - Christina Runkel; Christian Etmann; Michael Möller 001; Carola-Bibiane Schönlieb (CoRR, 2021)

Equivariant neural networks for inverse problems. - Elena Celledoni; Matthias J. Ehrhardt; Christian Etmann; Brynjulf Owren; Carola-Bibiane Schönlieb; Ferdia Sherry (CoRR, 2021)

Wasserstein GANs Work Because They Fail (to Approximate the Wasserstein Distance). - Jan Stanczuk; Christian Etmann; Lisa Maria Kreusser; Carola-Bibiane Schönlieb (CoRR, 2021)

CAFLOW: Conditional Autoregressive Flows. - Georgios Batzolis; Marcello Carioni; Christian Etmann; Soroosh Afyouni; Zoe Kourtzi; Carola-Bibiane Schönlieb (CoRR, 2021)

Conditional Image Generation with Score-Based Diffusion Models. - Georgios Batzolis; Jan Stanczuk; Carola-Bibiane Schönlieb; Christian Etmann (CoRR, 2021)

Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans. - Michael Roberts; Derek Driggs; Matthew Thorpe; Julian D. Gilbey; Michael Yeung; Stephan Ursprung; Angelica I. Avilés-Rivero; Christian Etmann; Cathal McCague; Lucian Beer; Jonathan R. Weir-McCall; Zhongzhao Teng; et al. (Nat. Mach. Intell., 2021)

Non-Uniform Diffusion Models. - Georgios Batzolis; Jan Stanczuk; Carola-Bibiane Schönlieb; Christian Etmann (CoRR, 2022)

Learning Posterior Distributions in Underdetermined Inverse Problems. - Christina Runkel; Michael Möller 001; Carola-Bibiane Schönlieb; Christian Etmann (SSVM, 2023)