| Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology B Rieck, M Togninalli, C Bock, M Moor, M Horn, T Gumbsch, K Borgwardt Proceedings of the International Conference on Learning Representations, 2019., 2018 | 17 | 2018 |
| Early Recognition of Sepsis with Gaussian Process Temporal Convolutional Networks and Dynamic Time Warping M Moor, M Horn, B Rieck, D Roqueiro, K Borgwardt Proceedings of the 4th Machine Learning for Healthcare Conference, 2019., 2019 | 12* | 2019 |
| Association mapping in biomedical time series via statistically significant shapelet mining C Bock, T Gumbsch, M Moor, B Rieck, D Roqueiro, K Borgwardt Bioinformatics 34 (13), i438-i446, 2018 | 9 | 2018 |
| Topological Autoencoders M Moor, M Horn, B Rieck, K Borgwardt arXiv preprint arXiv:1906.00722, 2019 | 4 | 2019 |
| Quantification of Liver, Subcutaneous, and Visceral Adipose Tissues by MRI Before and After Bariatric Surgery AC Meyer-Gerspach, R Peterli, M Moor, P Madörin, A Schötzau, D Nabers, ... Obesity surgery, 1-11, 2019 | 3 | 2019 |
| Early prediction of circulatory failure in the intensive care unit using machine learning SL Hyland, M Faltys, M Hüser, X Lyu, T Gumbsch, C Esteban, C Bock, ... Nature Medicine, 1-10, 2020 | 1 | 2020 |
| Set Functions for Time Series M Horn, M Moor, C Bock, B Rieck, K Borgwardt arXiv preprint arXiv:1909.12064, 2019 | 1 | 2019 |
| Machine learning for early prediction of circulatory failure in the intensive care unit SL Hyland, M Faltys, M Hüser, X Lyu, T Gumbsch, C Esteban, C Bock, ... arXiv preprint arXiv:1904.07990, 2019 | 1 | 2019 |
| Path Imputation Strategies for Signature Models of Irregular Time Series M Moor, M Horn, C Bock, K Borgwardt, B Rieck arXiv preprint arXiv:2005.12359, 2020 | | 2020 |
Bastian RieckMachine Learning & Computational Biology Lab, D-BSSE, ETH ZürichBestätigte E-Mail-Adresse bei bsse.ethz.ch
