Determinants of HIV-1 reservoir size and long-term dynamics during suppressive ART N Bachmann, C Von Siebenthal, V Vongrad, T Turk, K Neumann, ... Nature communications 10 (1), 3193, 2019 | 164 | 2019 |
Learning sparse latent representations with the deep copula information bottleneck A Wieczorek*, M Wieser*, D Murezzan, V Roth International Conference on Learning Representations (ICLR), 2018 | 37* | 2018 |
Information bottleneck for estimating treatment effects with systematically missing covariates S Parbhoo, M Wieser, A Wieczorek, V Roth Entropy 22 (4), 389, 2020 | 32* | 2020 |
3DMolNet: a generative network for molecular structures V Nesterov, M Wieser, V Roth arXiv preprint arXiv:2010.06477, 2020 | 30 | 2020 |
Learning extremal representations with deep archetypal analysis SM Keller, M Samarin, FA Torres, M Wieser, V Roth International Journal of Computer Vision (IJCV) 129 (4), 805-820, 2021 | 27 | 2021 |
Deep Archetypal Analysis SM Keller, M Samarin, M Wieser, V Roth German Conference on Pattern Recognition, 2019 | 23 | 2019 |
Greedy Structure Learning of Hierarchical Compositional Models A Kortylewski, A Wieczorek, M Wieser, C Blumer, S Parbhoo, ... IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019 | 13* | 2019 |
Informed MCMC with Bayesian Neural Networks for Facial Image Analysis A Kortylewski, M Wieser, A Morel-Forster, A Wieczorek, S Parbhoo, ... NeurIPS Bayesian Deep Learning Workshop, 2018 | 13 | 2018 |
Transfer Learning from Well-Curated to Less-Resourced Populations with HIV S Parbhoo, M Wieser, V Roth, F Doshi-Velez Machine Learning for Healthcare (MLHC), 2020 | 12 | 2020 |
Inverse Learning of Symmetries M Wieser, S Parbhoo, A Wieczorek, V Roth Advances in Neural Information Processing Systems 33, 2020 | 8* | 2020 |
Host genomics of the HIV-1 reservoir size and its decay rate during suppressive antiretroviral treatment CW Thorball, A Borghesi, N Bachmann, C Von Siebenthal, V Vongrad, ... JAIDS Journal of Acquired Immune Deficiency Syndromes 85 (4), 517-524, 2020 | 7 | 2020 |
Self-Supervised Representation Learning for High-Content Screening D Siegismund*, M Wieser*, S Heyse, S Steigele Medical Imaging with Deep Learning (MIDL), 2022 | 5 | 2022 |
Vision transformers show improved robustness in high-content image analysis M Wieser, D Siegismund, S Heyse, S Steigele 2022 9th Swiss Conference on Data Science (SDS), 71-72, 2022 | 2 | 2022 |
Learning conditional invariance through cycle consistency M Samarin, V Nesterov, M Wieser, A Wieczorek, S Parbhoo, V Roth DAGM German Conference on Pattern Recognition, 376-391, 2021 | 2 | 2021 |
Learning Channel Importance for High Content Imaging with Interpretable Deep Input Channel Mixing D Siegismund, M Wieser, S Heyse, S Steigele German Conference on Pattern Recognition, 2023 | 1 | 2023 |
Learning invariant representations for deep latent variable models M Wieser University_of_Basel, 2020 | 1 | 2020 |
A modular prototyping hard-and software platform for faster development of intelligent charging infrastructures of electric vehicles J Clement, M Wieser, P Benoit, R Kohrs, C Wittwer 4th International Conference on Power Engineering, Energy and Electrical …, 2013 | 1 | 2013 |
Estimating Causal Effects With Partial Covariates For Clinical Interpretability S Parbhoo, M Wieser, V Roth NeurIPS Machine Learning for Health Workshop (ML4H), 2018 | | 2018 |