Publications of Karsten Borgwardt

He, X.; Gumbsch, T.; Roqueiro, D.; Borgwardt, K.: Kernel conditional clustering and kernel conditional semi-supervised learning. Knowledge and Information Systems 62 (3), pp. 899 - 925 (2020)

Höllerer, S.; Papaxanthos, L.; Gumpinger, A. C.; Fischer, K.; Beisel, C.; Borgwardt, K.; Benenson, Y.; Jeschek, M.: Large-scale DNA-based phenotypic recording and deep learning enable highly accurate sequence-function mapping. Nature Communications 11, 3551 (2020)

Horn, M.; Moor, M.; Bock, C.; Rieck, B.; Borgwardt, K.: Set Functions for Time Series. Proceedings of the 37th International Conference on Machine Learning, PMLR (2020)

Hyland, S. L.; Faltys, M.; Hüser, M.; Lyu, X.; Gumbsch, T.; Esteban, C.; Bock, C.; Horn, M.; Moor, M.; Rieck, B. et al.; Zimmermann, M.; Bodenham, D.; Borgwardt, K.; Rätsch, G.; Merz, T. M.: Early prediction of circulatory failure in the intensive care unit using machine learning. Nature Medicine 26 (3), pp. 364 - 373 (2020)

Jutzeler, C. R.; Bourguignon, L.; Weis, C. V.; Tong, B.; Wong, C.; Rieck, B.; Pargger, H.; Tschudin-Sutter, S.; Egli, A.; Borgwardt, K. et al.; Walter, M.: Comorbidities, clinical signs and symptoms, laboratory findings, imaging features, treatment strategies, and outcomes in adult and pediatric patients with COVID-19: A systematic review and meta-analysis. Travel Medicine and Infectious Disease 37, 101825 (2020)

Moor, M.; Horn, M.; Rieck, B.; Borgwardt, K.: Topological Autoencoders. Proceedings of the 37th International Conference on Machine Learning, PMLR 119, pp. 7045 - 7054 (2020)

Rieck, B.; Yates, T.; Bock, C.; Borgwardt, K.; Wolf, G.; Turk-Browne, N.; Krishnaswamy, S.: Uncovering the Topology of Time-Varying fMRI Data using Cubical Persistence. Advances in Neural Information Processing Systems (NeurIPS 2020) 33, pp. 6900 - 6912 (2020)

Weis, C.; Horn, M.; Rieck, B.; Cuénod, A.; Egli, A.; Borgwardt, K.: Topological and kernel-based microbial phenotype prediction from MALDI-TOF mass spectra. Bioinformatics 36 (Supplement_1), pp. i30 - i38 (2020)

Bock, C.; Togninalli, M.; Ghisu, E.; Gumbsch, T.; Rieck, B.; Borgwardt, K.: A Wasserstein Subsequence Kernel for Time Series. 2019 IEEE International Conference on Data Mining (ICDM), pp. 964 - 969 (2019)

Llinares-López, F.; Papaxanthos, L.; Roqueiro, D.; Bodenham, D.; Borgwardt, K.: CASMAP: detection of statistically significant combinations of SNPs in association mapping. Bioinformatics 35 (15), pp. 2680 - 2682 (2019)

Moor, M.; Horn, M.; Rieck, B.; Roqueiro, D.; Borgwardt, K.: Early Recognition of Sepsis with Gaussian Process Temporal Convolutional Networks and Dynamic Time Warping. Proceedings of the 4th Machine Learning for Healthcare Conference , PMLR 106, pp. 2 - 26 (2019)

Rieck, B.; Bock, C.; Borgwardt, K.: A Persistent Weisfeiler-Lehman Procedure for Graph Classification. Proceedings of the 36th International Conference on Machine Learning (ICML 2019), PMLR 97 97, pp. 5448 - 5458 (2019)

Rieck, B. A.; Togninalli, M.; Bock, C.; Moor, M.; Horn, M.; Gumbsch, T.; Borgwardt, K.: Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology. International Conference on Learning Representations (ICLR) 2019 (2019)

Sugiyama, M.; Borgwardt, K.: Finding Statistically Significant Interactions between Continuous Features. Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence (IJCAI-19), pp. 3490 - 3498 (2019)

Togninalli, M.; Ghisu, E.; Llinares-López, F.; Rieck, B.; Borgwardt, K.: Wasserstein Weisfeiler-Lehman Graph Kernels. Advances in Neural Information Processing Systems 32 (NeurIPS 2019) (2019)

Togninalli, M.; Yoneoka, D.; Kolios, A. G. A.; Borgwardt, K.; Nilsson, J.: Pretransplant Kinetics of Anti-HLA Antibodies in Patients on the Waiting List for Kidney Transplantation. Journal of the American Society of Nephrology 30 (11), pp. 2262 - 2274 (2019)

He, X.; Folkman, L.; Borgwardt, K.: Kernelized rank learning for personalized drug recommendation. Bioinformatics 34 (16), pp. 2808 - 2816 (2018)

Gärtner, M.; Ghisu, M. E.; Scheidegger, M.; Bönke, L.; Fan, Y.; Stippl, A.; Herrera-Melendez, A.-L.; Metz, S.; Winnebeck, E.; Fissler, M. et al.; Henning, A.; Bajbouj, M.; Borgwardt, K.; Barnhofer, T.; Grimm, S.: Aberrant working memory processing in major depression: evidence from multivoxel pattern classification. Neuropsychopharmacology 43 (9), pp. 1972 - 1979 (2018)

Bock, C.; Gumbsch, T.; Moor, M.; Rieck, B.; Roqueiro, D.; Borgwardt, K.: Association mapping in biomedical time series via statistically significant shapelet mining. Bioinformatics 34 (13), pp. i438 - i446 (2018)

Togninalli, M.; Seren, Ü.; Hu, M.; Fitz, J.; Nordborg, M.; Weigel, D.; Borgwardt, K.; Korte, A.; Grimm, D.: The AraGWAS Catalog: A curated and standardized Arabidopsis thaliana GWAS catalog. Nucleic Acids Research 46 (D1), pp. D1150 - D1156 (2018)