| 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 | 176 | 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 | 38* | 2018 |
| 3DMolNet: a generative network for molecular structures V Nesterov, M Wieser, V Roth arXiv preprint arXiv:2010.06477, 2020 | 35 | 2020 |
| 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 |
| 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 | 30 | 2021 |
| Deep Archetypal Analysis SM Keller, M Samarin, M Wieser, V Roth German Conference on Pattern Recognition, 2019 | 24 | 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 | 14 | 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 | 13 | 2020 |
| 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 |
| 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 |
| Determinants of HIV-1 reservoir size and long-term dynamics during suppressive ART. Nat Commun 10: 3193 N Bachmann, C von Siebenthal, V Vongrad, T Turk, K Neumann, ... | 5 | 2019 |
| 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 | 2 | 2023 |
| 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 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 |
| PCIM: Learning Pixel Attributions via Pixel-wise Channel Isolation Mixing in High Content Imaging D Siegismund, M Wieser, S Heyse, S Steigele arXiv preprint arXiv:2412.02275, 2024 | | 2024 |
| Estimating Causal Effects With Partial Covariates For Clinical Interpretability S Parbhoo, M Wieser, V Roth NeurIPS Machine Learning for Health Workshop (ML4H), 2018 | | 2018 |
Volker RothProfessor for Computer Science, University of BaselVerified email at unibas.ch
