Predicting Sequences of Clinical Events by Using a Personalized Temporal Latent Embedding Model. - Cristóbal Esteban; Danilo Schmidt; Denis Krompass; Volker Tresp (ICHI, 2015)

Learning with Memory Embeddings. - Volker Tresp; Cristóbal Esteban; Yinchong Yang; Stephan Baier; Denis Krompaß (CoRR, 2015)

Exploiting Latent Embeddings of Nominal Clinical Data for Predicting Hospital Readmission. - Denis Krompaß; Cristóbal Esteban; Volker Tresp; Martin Sedlmayr; Thomas Ganslandt (Künstliche Intell., 2015)

Embedding Mapping Approaches for Tensor Factorization and Knowledge Graph Modelling. - Yinchong Yang; Cristóbal Esteban; Volker Tresp (ESWC, 2016)

Predicting the co-evolution of event and Knowledge Graphs. - Cristóbal Esteban; Volker Tresp; Yinchong Yang; Stephan Baier; Denis Krompass (FUSION, 2016)

Predicting Clinical Events by Combining Static and Dynamic Information Using Recurrent Neural Networks. - Cristóbal Esteban; Oliver Staeck; Stephan Baier; Yinchong Yang; Volker Tresp (ICHI, 2016)

Real-valued (Medical) Time Series Generation with Recurrent Conditional GANs. - Cristóbal Esteban; Stephanie L. Hyland; Gunnar Rätsch (CoRR, 2017)

A Machine Learning-based Early Warning System for Circulatory System Deterioration in Intensive Care Unit Patients. - Stephanie L. Hyland; Martin Faltys; Matthias Hüser; Xinrui Lyu; Cristóbal Esteban; Gunnar Rätsch; Tobias Merz (AMIA, 2018)

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; et al. (CoRR, 2019)