| Speaker Identification and Clustering using Convolution Neural Networks Y Lukic, C Vogt, O Dürr, T Stadelmann IEEE International workshop on Machine Learning for Signal Processing, 2016 | 171 | 2016 |
| Probabilistic deep learning: With python, keras and tensorflow probability O Dürr, B Sick, E Murina Manning Publications, 2020 | 115 | 2020 |
| Single-Cell Phenotype Classification Using Deep Convolutional Neural Networks O Dürr, B Sick Journal of biomolecular screening 21 (9), 998-1003, 2016 | 94 | 2016 |
| Percolation concepts in solid state ionics W Dieterich, O Dürr, P Pendzig, A Bunde, A Nitzan Physica A: Statistical Mechanics and its Applications 266 (1-4), 229-237, 1999 | 51 | 1999 |
| Integrating uncertainty in deep neural networks for MRI based stroke analysis L Herzog, E Murina, O Dürr, S Wegener, B Sick Medical image analysis 65, 101790, 2020 | 49 | 2020 |
| Robust hit identification by quality assurance and multivariate data analysis of a high-content, cell-based assay O Dürr, F Duval, A Nichols, P Lang, A Brodte, S Heyse, D Besson SLAS Discovery 12 (8), 1042-1049, 2007 | 44 | 2007 |
| Bone erosion scoring for rheumatoid arthritis with deep convolutional neural networks J Rohrbach, T Reinhard, B Sick, O Dürr Computers & Electrical Engineering 78, 472-481, 2019 | 40 | 2019 |
| Deep and interpretable regression models for ordinal outcomes L Kook, L Herzog, T Hothorn, O Dürr, B Sick Pattern Recognition 122, 108263, 2022 | 34 | 2022 |
| Potential and Limitations of Commercial Sentiment Detection Tools. M Cieliebak, O Dürr, F Uzdilli ESSEM@ AI* IA, 47-58, 2013 | 34 | 2013 |
| Effective medium theory of conduction in stretched polymer electrolytes O Dürr, W Dieterich, P Maass, A Nitzan The Journal of Physical Chemistry B 106 (24), 6149-6155, 2002 | 34 | 2002 |
| Learning neural models for end-to-end clustering BB Meier, I Elezi, M Amirian, O Dürr, T Stadelmann Artificial Neural Networks in Pattern Recognition: 8th IAPR TC3 Workshop …, 2018 | 27 | 2018 |
| Dynamic percolation theory for particle diffusion in a polymer network O Dürr, T Volz, W Dieterich, A Nitzan The Journal of chemical physics 117 (1), 441-447, 2002 | 26 | 2002 |
| Coupled ion and network dynamics in polymer electrolytes: Monte Carlo study of a lattice model O Dürr, W Dieterich, A Nitzan The Journal of chemical physics 121 (24), 12732-12739, 2004 | 25 | 2004 |
| Beyond ImageNet: deep learning in industrial practice T Stadelmann, V Tolkachev, B Sick, J Stampfli, O Dürr Applied data science: lessons learned for the data-driven business, 205-232, 2019 | 24 | 2019 |
| Applied data science in Europe: Challenges for academia in keeping up with a highly demanded topic T Stadelmann, K Stockinger, M Braschler, M Cieliebak, G Baudinot, ... 9th European Computer Science Summit, Amsterdam, Niederlande, 8-9 October 2013, 2013 | 21 | 2013 |
| Deep transformation models: Tackling complex regression problems with neural network based transformation models B Sick, T Hathorn, O Dürr 2020 25th International Conference on Pattern Recognition (ICPR), 2476-2481, 2021 | 20 | 2021 |
| Know when you don't know: a robust deep learning approach in the presence of unknown phenotypes O Dürr, E Murina, D Siegismund, V Tolkachev, S Steigele, B Sick Assay and drug development technologies 16 (6), 343-349, 2018 | 20 | 2018 |
| Deep Learning on a Raspberry Pi for Real Time Face Recognition. O Dürr, Y Pauchard, D Browarnik, R Axthelm, M Loeser Eurographics (Posters), 11-12, 2015 | 20 | 2015 |
| Single shot mc dropout approximation K Brach, B Sick, O Dürr arXiv preprint arXiv:2007.03293, 2020 | 19 | 2020 |
| Learning embeddings for speaker clustering based on voice equality YX Lukic, C Vogt, O Dürr, T Stadelmann 2017 IEEE 27th International Workshop on Machine Learning for Signal …, 2017 | 19 | 2017 |
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