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Matthias Hüser
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Books and Theses
- 2021
- [b1]Matthias Hüser:
Machine Learning Approaches for Patient Monitoring in the Intensive Care Unit. ETH Zurich, Zürich, Switzerland, 2021
Conference and Workshop Papers
- 2021
- [c7]Laura Manduchi, Matthias Hüser, Martin Faltys, Julia E. Vogt
, Gunnar Rätsch, Vincent Fortuin:
T-DPSOM: an interpretable clustering method for unsupervised learning of patient health states. CHIL 2021: 236-245 - [c6]Hugo Yèche, Gideon Dresdner, Francesco Locatello, Matthias Hüser, Gunnar Rätsch:
Neighborhood Contrastive Learning Applied to Online Patient Monitoring. ICML 2021: 11964-11974 - [c5]Hugo Yèche, Rita Kuznetsova, Marc Zimmermann, Matthias Hüser, Xinrui Lyu, Martin Faltys, Gunnar Rätsch:
HiRID-ICU-Benchmark - A Comprehensive Machine Learning Benchmark on High-resolution ICU Data. NeurIPS Datasets and Benchmarks 2021 - [c4]Jonathan Heitz, Joanna Ficek, Martin Faltys, Tobias M. Merz, Gunnar Rätsch, Matthias Hüser:
WRSE - a non-parametric weighted-resolution ensemble for predicting individual survival distributions in the ICU. SPACA 2021: 54-69 - 2019
- [c3]Vincent Fortuin
, Matthias Hüser, Francesco Locatello, Heiko Strathmann, Gunnar Rätsch:
SOM-VAE: Interpretable Discrete Representation Learning on Time Series. ICLR (Poster) 2019 - 2018
- [c2]Stephanie L. Hyland, Martin Faltys, Matthias Hüser, Xinrui Lyu, Cristóbal Esteban, Gunnar Rätsch, Tobias Merz:
A Machine Learning-based Early Warning System for Circulatory System Deterioration in Intensive Care Unit Patients. AMIA 2018 - [c1]Stephanie L. Hyland, Matthias Hüser, Xinrui Lyu, Martin Faltys, Tobias Merz, Gunnar Rätsch:
Predicting circulatory system deterioration in intensive care unit patients. AIH@IJCAI 2018: 87-92
Informal and Other Publications
- 2021
- [i9]Matthias Hüser, Martin Faltys, Xinrui Lyu, Chris Barber, Stephanie L. Hyland, Tobias M. Merz, Gunnar Rätsch:
Early prediction of respiratory failure in the intensive care unit. CoRR abs/2105.05728 (2021) - [i8]Hugo Yèche, Gideon Dresdner, Francesco Locatello, Matthias Hüser, Gunnar Rätsch:
Neighborhood Contrastive Learning Applied to Online Patient Monitoring. CoRR abs/2106.05142 (2021) - [i7]Hugo Yèche, Rita Kuznetsova, Marc Zimmermann, Matthias Hüser, Xinrui Lyu, Martin Faltys, Gunnar Rätsch:
HiRID-ICU-Benchmark - A Comprehensive Machine Learning Benchmark on High-resolution ICU Data. CoRR abs/2111.08536 (2021) - 2020
- [i6]Jonathan Heitz, Joanna Ficek, Martin Faltys, Tobias M. Merz, Gunnar Rätsch, Matthias Hüser:
WRSE - a non-parametric weighted-resolution ensemble for predicting individual survival distributions in the ICU. CoRR abs/2011.00865 (2020) - 2019
- [i5]Matthias Hüser, Adrian Kündig, Walter Karlen, Valeria De Luca, Martin Jaggi:
Forecasting intracranial hypertension using multi-scale waveform metrics. CoRR abs/1902.09499 (2019) - [i4]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) - [i3]Laura Manduchi, Matthias Hüser, Gunnar Rätsch, Vincent Fortuin:
Variational PSOM: Deep Probabilistic Clustering with Self-Organizing Maps. CoRR abs/1910.01590 (2019) - 2018
- [i2]Vincent Fortuin, Matthias Hüser, Francesco Locatello, Heiko Strathmann, Gunnar Rätsch:
Deep Self-Organization: Interpretable Discrete Representation Learning on Time Series. CoRR abs/1806.02199 (2018) - [i1]Xinrui Lyu, Matthias Hüser, Stephanie L. Hyland, George Zerveas
, Gunnar Rätsch:
Improving Clinical Predictions through Unsupervised Time Series Representation Learning. CoRR abs/1812.00490 (2018)
Coauthor Index
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