Post-antibiotic gut mucosal microbiome reconstitution is impaired by probiotics and improved by autologous FMT J Suez, N Zmora, G Zilberman-Schapira, U Mor, M Dori-Bachash, ... Cell 174 (6), 1406-1423. e16, 2018 | 1019 | 2018 |
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 | 375 | 2020 |
Topological autoencoders M Moor, M Horn, B Rieck, K Borgwardt International Conference on Machine Learning, 7045-7054, 2020 | 201 | 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 International Conference on Learning Representations, 2019 | 151 | 2019 |
Set functions for time series M Horn, M Moor, C Bock, B Rieck, K Borgwardt International Conference on Machine Learning, 4353-4363, 2020 | 147 | 2020 |
Early prediction of sepsis in the ICU using machine learning: a systematic review M Moor, B Rieck, M Horn, CR Jutzeler, K Borgwardt Frontiers in medicine 8, 607952, 2021 | 145 | 2021 |
Bridging the gap to real-world object-centric learning M Seitzer, M Horn, A Zadaianchuk, D Zietlow, T Xiao, CJ Simon-Gabriel, ... arXiv preprint arXiv:2209.14860, 2022 | 118 | 2022 |
Early recognition of sepsis with Gaussian process temporal convolutional networks and dynamic time warping M Moor, M Horn, B Rieck, D Roqueiro, K Borgwardt Machine learning for healthcare conference, 2-26, 2019 | 114* | 2019 |
Topological graph neural networks M Horn, E De Brouwer, M Moor, Y Moreau, B Rieck, K Borgwardt arXiv preprint arXiv:2102.07835, 2021 | 104 | 2021 |
Assaying out-of-distribution generalization in transfer learning F Wenzel, A Dittadi, P Gehler, CJ Simon-Gabriel, M Horn, D Zietlow, ... Advances in Neural Information Processing Systems 35, 7181-7198, 2022 | 70 | 2022 |
TRAPP webserver: predicting protein binding site flexibility and detecting transient binding pockets A Stank, DB Kokh, M Horn, E Sizikova, R Neil, J Panecka, S Richter, ... Nucleic acids research 45 (W1), W325-W330, 2017 | 58 | 2017 |
Evaluation metrics for graph generative models: Problems, pitfalls, and practical solutions L O'Bray, M Horn, B Rieck, K Borgwardt arXiv preprint arXiv:2106.01098, 2021 | 43 | 2021 |
Image retrieval outperforms diffusion models on data augmentation MF Burg, F Wenzel, D Zietlow, M Horn, O Makansi, F Locatello, C Russell Transactions on Machine Learning Research, 2023 | 35* | 2023 |
Topological and kernel-based microbial phenotype prediction from MALDI-TOF mass spectra C Weis, M Horn, B Rieck, A Cuénod, A Egli, K Borgwardt Bioinformatics 36 (Supplement_1), i30-i38, 2020 | 29 | 2020 |
Backbone circularization of Bacillus subtilis family 11 xylanase increases its thermostability and its resistance against aggregation MC Waldhauer, SN Schmitz, C Ahlmann-Eltze, JG Gleixner, CC Schmelas, ... Molecular BioSystems 11 (12), 3231-3243, 2015 | 27 | 2015 |
Predicting sepsis using deep learning across international sites: a retrospective development and validation study M Moor, N Bennett, D Plečko, M Horn, B Rieck, N Meinshausen, ... EClinicalMedicine 62, 2023 | 24 | 2023 |
Causal triplet: An open challenge for intervention-centric causal representation learning Y Liu, A Alahi, C Russell, M Horn, D Zietlow, B Schölkopf, F Locatello Conference on Causal Learning and Reasoning, 553-573, 2023 | 16 | 2023 |
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 | 11 | 2020 |
Pathologies in priors and inference for Bayesian transformers T Cinquin, A Immer, M Horn, V Fortuin arXiv preprint arXiv:2110.04020, 2021 | 9 | 2021 |
Object-centric multiple object tracking Z Zhao, J Wang, M Horn, Y Ding, T He, Z Bai, D Zietlow, CJ Simon-Gabriel, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 8 | 2023 |