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Christian Etmann
Christian Etmann
Research Scientist, Deep Render
Verified email at deeprender.ai
Title
Cited by
Cited by
Year
Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
M Roberts, D Driggs, M Thorpe, J Gilbey, M Yeung, S Ursprung, ...
Nature Machine Intelligence 3 (3), 199-217, 2021
3622021
On the Connection Between Adversarial Robustness and Saliency Map Interpretability
C Etmann, S Lunz, P Maass, CB Schönlieb
International Conference on Machine Learning 2019, 2019
962019
Deep learning for tumor classification in imaging mass spectrometry
J Behrmann, C Etmann, T Boskamp, R Casadonte, J Kriegsmann, P Maaβ
Bioinformatics 34 (7), 1215-1223, 2018
932018
Structure preserving deep learning
E Celledoni, MJ Ehrhardt, C Etmann, RI McLachlan, B Owren, ...
European Journal of Applied Mathematics, 2021
212021
iUNets: Fully invertible U-Nets with learnable up-and downsampling
C Etmann, R Ke, CB Schönlieb
arXiv preprint arXiv:2005.05220, 2020
19*2020
Wasserstein GANs work because they fail (to approximate the Wasserstein distance)
J Stanczuk, C Etmann, LM Kreusser, CB Schönlieb
arXiv preprint arXiv:2103.01678, 2021
152021
A closer look at double backpropagation
C Etmann
arXiv preprint arXiv:1906.06637, 2019
82019
Equivariant neural networks for inverse problems
E Celledoni, MJ Ehrhardt, C Etmann, B Owren, CB Schönlieb, F Sherry
Inverse Problems 37 (8), 085006, 2021
72021
Conditional image generation with score-based diffusion models
G Batzolis, J Stanczuk, CB Schönlieb, C Etmann
arXiv preprint arXiv:2111.13606, 2021
42021
Invertible Learned Primal-Dual
J Rudzusika, B Bajic, O Öktem, CB Schönlieb, C Etmann
NeurIPS 2021 Workshop on Deep Learning and Inverse Problems, 2021
32021
AIX-COVNET, James HF Rudd, Evis Sala, and Carola-Bibiane Schönlieb. Common pitfalls and recommendations for using machine learning to detect and prognosticate for covid-19 …
M Roberts, D Driggs, M Thorpe, J Gilbey, M Yeung, S Ursprung, ...
Nature Machine Intelligence 3 (199-217), 1-5, 2021
32021
Double Backpropagation with Applications to Robustness and Saliency Map Interpretability
C Etmann
Universität Bremen, 2019
32019
Deep relevance regularization: Interpretable and robust tumor typing of imaging mass spectrometry data
C Etmann, M Schmidt, J Behrmann, T Boskamp, L Hauberg-Lotte, A Peter, ...
arXiv preprint arXiv:1912.05459, 2019
22019
INSIDEnet: Interpretable NonexpanSIve Data‐Efficient network for denoising in grating interferometry breast CT
S van Gogh, Z Wang, M Rawlik, C Etmann, S Mukherjee, CB Schönlieb, ...
Medical physics, 2022
12022
Non-Uniform Diffusion Models
G Batzolis, J Stanczuk, CB Schönlieb, C Etmann
arXiv preprint arXiv:2207.09786, 2022
2022
CAFLOW: Conditional Autoregressive Flows
G Batzolis, M Carioni, C Etmann, S Afyouni, Z Kourtzi, CB Schönlieb
arXiv preprint arXiv:2106.02531, 2021
2021
Depthwise Separable Convolutions Allow for Fast and Memory-Efficient Spectral Normalization
C Runkel, C Etmann, M Möller, CB Schönlieb
arXiv preprint arXiv:2102.06496, 2021
2021
Full Text: Machine learning for COVID-19 detection and prognostication using chest radiographs and CT scans: a systematic methodological review-Onikle
M Roberts, D Driggs, M Thorpe, J Gilbey, M Yeung, S Ursprung, ...
2020
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