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Stephanie L. Hyland

Looking for Out-of-Distribution Environments in Critical Care: A case study with the eICU Database



Dimitris Spathis , Stephanie L. Hyland

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Early prediction of respiratory failure in the intensive care unit



Matthias Hüser , Martin Faltys , Xinrui Lyu , Chris Barber , Stephanie L. Hyland , Tobias M. Merz , Gunnar Rätsch

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* 14 pages, 5 figures 
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ML4H Abstract Track 2020



Emily Alsentzer , Matthew B. A. McDermott , Fabian Falck , Suproteem K. Sarkar , Subhrajit Roy , Stephanie L. Hyland


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On the Intrinsic Privacy of Stochastic Gradient Descent



Stephanie L. Hyland , Shruti Tople

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* 15 pages, 9 figures 
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Unsupervised Extraction of Phenotypes from Cancer Clinical Notes for Association Studies



Stefan G. Stark , Stephanie L. Hyland , Melanie F. Pradier , Kjong Lehmann , Andreas Wicki , Fernando Perez Cruz , Julia E. Vogt , Gunnar Rätsch

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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 Bodenham , Karsten Borgwardt , Gunnar Rätsch , Tobias M. Merz

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* 5 main figures, 1 main table, 13 supplementary figures, 5 supplementary tables; 250ppi images 
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Improving Clinical Predictions through Unsupervised Time Series Representation Learning



Xinrui Lyu , Matthias Hueser , Stephanie L. Hyland , George Zerveas , Gunnar Raetsch

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* Machine Learning for Health (ML4H) Workshop at NeurIPS 2018 arXiv:1811.07216 
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Real-valued (Medical) Time Series Generation with Recurrent Conditional GANs



Cristóbal Esteban , Stephanie L. Hyland , Gunnar Rätsch

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* 13 pages, 4 figures, 3 tables (update with differential privacy) 
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Learning Unitary Operators with Help From u(n)



Stephanie L. Hyland , Gunnar Rätsch

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* 9 pages, 3 figures, 5 figures inc. subfigures, to appear at AAAI-17 
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