Thomas Gumbsch

According to our database, Thomas Gumbsch authored at least 8 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

An empirical study on KDIGO-defined acute kidney injury prediction in the intensive care unit.

Xinrui Lyu, Bowen Fan, Matthias Hüser, Philip Hartout, Thomas Gumbsch, Martin Faltys, Tobias M. Merz, Gunnar Rätsch, Karsten M. Borgwardt

Bioinform., 2024

2020

Kernel conditional clustering and kernel conditional semi-supervised learning.

Xiao He, Thomas Gumbsch, Damian Roqueiro, Karsten M. Borgwardt

Knowl. Inf. Syst., 2020

Enhancing statistical power in temporal biomarker discovery through representative shapelet mining.

Thomas Gumbsch, Christian Bock, Michael Moor, Bastian Rieck, Karsten M. Borgwardt

Bioinform., 2020

2019

Machine learning for early prediction of circulatory failure in the intensive care unit.

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

CoRR, 2019

Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology.

Bastian Rieck, Matteo Togninalli, Christian Bock, Michael Moor, Max Horn, Thomas Gumbsch, Karsten M. Borgwardt

Proceedings of the 7th International Conference on Learning Representations, 2019

A Wasserstein Subsequence Kernel for Time Series.

Christian Bock, Matteo Togninalli, M. Elisabetta Ghisu, Thomas Gumbsch, Bastian Rieck, Karsten M. Borgwardt

Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

2018

Association mapping in biomedical time series via statistically significant shapelet mining.

Christian Bock, Thomas Gumbsch, Michael Moor, Bastian Rieck, Damian Roqueiro, Karsten M. Borgwardt

Bioinform., 2018

2017

Kernel Conditional Clustering.

Xiao He, Thomas Gumbsch, Damian Roqueiro, Karsten M. Borgwardt

Proceedings of the 2017 IEEE International Conference on Data Mining, 2017