Christian Etmann

18 papers A* 1Journal 15Unranked 2

Year	Rank	Type	Title / Venue / Authors
2023	—	`conf`	Learning Posterior Distributions in Underdetermined Inverse Problems. SSVM Christina Runkel, Michael Möller, Carola-Bibiane Schönlieb, Christian Etmann
2022	J	`jnl`	Non-Uniform Diffusion Models. CoRR Georgios Batzolis, Jan Stanczuk, Carola-Bibiane Schönlieb, Christian Etmann
2021	J	`jnl`	CAFLOW: Conditional Autoregressive Flows. CoRR Georgios Batzolis, Marcello Carioni, Christian Etmann, Soroosh Afyouni, Zoe Kourtzi, Carola-Bibiane Schönlieb
2021	J	`jnl`	Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans. Nat. Mach. Intell. 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, Effrossyni Gkrania-Klotsas, James H. F. Rudd, Evis Sala, Carola-Bibiane Schönlieb
2021	J	`jnl`	Conditional Image Generation with Score-Based Diffusion Models. CoRR Georgios Batzolis, Jan Stanczuk, Carola-Bibiane Schönlieb, Christian Etmann
2021	J	`jnl`	Depthwise Separable Convolutions Allow for Fast and Memory-Efficient Spectral Normalization. CoRR Christina Runkel, Christian Etmann, Michael Möller, Carola-Bibiane Schönlieb
2021	J	`jnl`	Equivariant neural networks for inverse problems. CoRR Elena Celledoni, Matthias J. Ehrhardt, Christian Etmann, Brynjulf Owren, Carola-Bibiane Schönlieb, Ferdia Sherry
2021	J	`jnl`	Wasserstein GANs Work Because They Fail (to Approximate the Wasserstein Distance). CoRR Jan Stanczuk, Christian Etmann, Lisa Maria Kreusser, Carola-Bibiane Schönlieb
2020	J	`jnl`	Machine learning for COVID-19 detection and prognostication using chest radiographs and CT scans: a systematic methodological review. CoRR 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, James H. F. Rudd, Evis Sala, Carola-Bibiane Schönlieb
2020	J	`jnl`	Structure preserving deep learning. CoRR Elena Celledoni, Matthias J. Ehrhardt, Christian Etmann, Robert I. McLachlan, Brynjulf Owren, Carola-Bibiane Schönlieb, Ferdia Sherry
2020	J	`jnl`	iUNets: Fully invertible U-Nets with Learnable Up- and Downsampling. CoRR Christian Etmann, Rihuan Ke, Carola-Bibiane Schönlieb
2020	—	`conf`	iUNets: Learnable Invertible Up- and Downsampling for Large-Scale Inverse Problems. MLSP Christian Etmann, Rihuan Ke, Carola-Bibiane Schönlieb
2019	J	`jnl`	A Closer Look at Double Backpropagation. CoRR Christian Etmann
2019	J	`jnl`	Deep Relevance Regularization: Interpretable and Robust Tumor Typing of Imaging Mass Spectrometry Data. CoRR Christian Etmann, Maximilian Schmidt, Jens Behrmann, Tobias Boskamp, Lena Hauberg-Lotte, Annette Peter, Rita Casadonte, Jörg Kriegsmann, Peter Maass
2019	A*	`conf`	On the Connection Between Adversarial Robustness and Saliency Map Interpretability. ICML Christian Etmann, Sebastian Lunz, Peter Maass, Carola Schönlieb
2019	J	`jnl`	On the Connection Between Adversarial Robustness and Saliency Map Interpretability. CoRR Christian Etmann, Sebastian Lunz, Peter Maass, Carola-Bibiane Schönlieb
2018	J	`jnl`	Deep learning for tumor classification in imaging mass spectrometry. Bioinform. Jens Behrmann, Christian Etmann, Tobias Boskamp, Rita Casadonte, Jörg Kriegsmann, Peter Maaß
2017	J	`jnl`	Deep Learning for Tumor Classification in Imaging Mass Spectrometry. CoRR Jens Behrmann, Christian Etmann, Tobias Boskamp, Rita Casadonte, Jörg Kriegsmann, Peter Maass