no code implementations • 16 Apr 2019 • 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
Intensive care clinicians are presented with large quantities of patient information and measurements from a multitude of monitoring systems.
6 code implementations • ICLR 2018 • Cristóbal Esteban, Stephanie L. Hyland, Gunnar Rätsch
We also describe novel evaluation methods for GANs, where we generate a synthetic labelled training dataset, and evaluate on a real test set the performance of a model trained on the synthetic data, and vice-versa.
no code implementations • 8 Feb 2016 • Cristóbal Esteban, Oliver Staeck, Yinchong Yang, Volker Tresp
In this work we present an approach based on RNNs, specifically designed for the clinical domain, that combines static and dynamic information in order to predict future events.
no code implementations • 21 Dec 2015 • Cristóbal Esteban, Volker Tresp, Yinchong Yang, Stephan Baier, Denis Krompaß
By predicting future events, we also predict likely changes in the knowledge graph and thus obtain a model for the evolution of the knowledge graph as well.
no code implementations • 25 Nov 2015 • Volker Tresp, Cristóbal Esteban, Yinchong Yang, Stephan Baier, Denis Krompaß
We introduce a number of hypotheses on human memory that can be derived from the developed mathematical models.