| 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 26 (3), 364-373, 2020 | 48* | 2020 |
| 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 | 43 | 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 | 28* | 2019 |
| Topological Autoencoders M Moor, M Horn, B Rieck, K Borgwardt International Conference on Machine Learning (ICML), 7045--7054, 2020 | 23 | 2020 |
| 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 | 18 | 2018 |
| Set Functions for Time Series M Horn, M Moor, C Bock, B Rieck, K Borgwardt International Conference on Machine Learning (ICML), 4353-4363, 2020 | 11 | 2020 |
| 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 29 (9), 2795-2805, 2019 | 7 | 2019 |
| Path Imputation Strategies for Signature Models M Moor, M Horn, C Bock, K Borgwardt, B Rieck ICML 2020 Workshop on the Art of Learning with Missing Values (Artemiss), 2020 | 3 | 2020 |
| 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 | 3 | 2020 |
| Accelerating Detection of Lung Pathologies with Explainable Ultrasound Image Analysis J Born, N Wiedemann, M Cossio, C Buhre, G Brändle, K Leidermann, ... Applied Sciences 11 (2), 672, 2021 | 2 | 2021 |
| Topological Graph Neural Networks M Horn, E De Brouwer, M Moor, Y Moreau, B Rieck, K Borgwardt arXiv preprint arXiv:2102.07835, 2021 | 1 | 2021 |
| Challenging Euclidean Topological Autoencoders M Moor, M Horn, K Borgwardt, B Rieck Topological Data Analysis and Beyond Workshop at NeurIPS 2020, 2020 | 1* | 2020 |
| Early Prediction of Sepsis in the ICU using Machine Learning: A Systematic Review. M Moor, B Rieck, M Horn, C Jutzeler, K Borgwardt medRxiv, 2020 | 1 | 2020 |
| Machine Learning for Biomedical Time Series Classification: From Shapelets to Deep Learning C Bock, M Moor, CR Jutzeler, K Borgwardt Artificial Neural Networks, 33-71, 2020 | 1 | 2020 |
| A Survey of Topological Machine Learning Methods F Hensel, M Moor, B Rieck Frontiers in Artificial Intelligence 4, 52, 2021 | | 2021 |
| Enhancing statistical power in temporal biomarker discovery through representative shapelet mining T Gumbsch, C Bock, M Moor, B Rieck, K Borgwardt Bioinformatics 36 (Supplement_2), i840-i848, 2020 | | 2020 |
| Learning Individualized Treatment Rules with Estimated Translated Inverse Propensity Score Z Wu, Y Yang, Y Ma, Y Liu, R Zhao, M Moor, V Tresp arXiv preprint arXiv:2007.01083, 2020 | | 2020 |
Karsten BorgwardtProfessor, ETH ZurichBestätigte E-Mail-Adresse bei bsse.ethz.ch
