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2020 – today
- 2020
[j2]Xiao He
, Thomas Gumbsch, Damian Roqueiro, Karsten M. Borgwardt:
Kernel conditional clustering and kernel conditional semi-supervised learning. Knowl. Inf. Syst. 62(3): 899-925 (2020)
2010 – 2019
- 2019
- [c3]Christian Bock, Matteo Togninalli, M. Elisabetta Ghisu, Thomas Gumbsch, Bastian Rieck, Karsten M. Borgwardt:
A Wasserstein Subsequence Kernel for Time Series. ICDM 2019: 964-969 - [c2]Bastian Rieck, Matteo Togninalli, Christian Bock, Michael Moor, Max Horn, Thomas Gumbsch, Karsten M. Borgwardt:
Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology. ICLR (Poster) 2019 - [i2]Stephanie L. Hyland, Martin Faltys, Matthias Hüser, Xinrui Lyu, Thomas Gumbsch, Cristóbal Esteban, Christian Bock, Max Horn, Michael Moor, Bastian Rieck, Marc Zimmermann, Dean A. Bodenham, Karsten M. Borgwardt, Gunnar Rätsch, Tobias M. Merz:
Machine learning for early prediction of circulatory failure in the intensive care unit. CoRR abs/1904.07990 (2019) - 2018
- [j1]Christian Bock, Thomas Gumbsch, Michael Moor, Bastian Rieck, Damian Roqueiro, Karsten M. Borgwardt:
Association mapping in biomedical time series via statistically significant shapelet mining. Bioinform. 34(13): i438-i446 (2018) - [i1]Bastian Rieck, Matteo Togninalli, Christian Bock, Michael Moor, Max Horn, Thomas Gumbsch, Karsten M. Borgwardt:
Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology. CoRR abs/1812.09764 (2018) - 2017
- [c1]Xiao He, Thomas Gumbsch, Damian Roqueiro, Karsten M. Borgwardt:
Kernel Conditional Clustering. ICDM 2017: 157-166
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