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Publications by Tresp, Volker

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Number of items: 10.

Journal article

Trautmann, Dietrich; Fromm, Michael; Tresp, Volker; Seidl, Thomas; Schütze, Hinrich (2020): Relational and Fine-Grained Argument Mining. The LMU Munich project ReMLAV within the DFG Priority Program RATIO “Robust Argumentation Machines”. In: Datenbank-Spektrum, Vol. 20, No. 2: pp. 99-105 [PDF, 365kB]

Rohm, Markus; Tresp, Volker; Müller, Michael; Kern, Christoph; Manakov, Ilja; Weiss, Maximilian; Sim, Dawn A.; Priglinger, Siegfried; Keane, Pearse A.; Kortüm, Karsten (2018): Predicting Visual Acuity by Using Machine Learning in Patients Treated for Neovascular Age-Related Macular Degeneration. In: Ophthalmology, Vol. 125, No. 7: pp. 1028-1036

Nickel, Maximilian; Murphy, Kevin; Tresp, Volker; Gabrilovich, Evgeniy (2016): A Review of Relational Machine Learning for Knowledge Graphs. In: Proceedings of the Ieee, Vol. 104, No. 1: pp. 11-33

Haykin, Simon; Tresp, Volker; Benediktsson, Jon Atli (2016): Big Data: Practical Applications. In: Proceedings of the Ieee, Vol. 104, No. 11: pp. 2082-2084

Tresp, Volker; Overhage, J. Marc; Bundschus, Markus; Rabizadeh, Shahrooz; Fasching, Peter A.; Yu, Shipeng (2016): Going Digital: A Survey on Digitalization and Large-Scale Data Analytics in Healthcare. In: Proceedings of the Ieee, Vol. 104, No. 11: pp. 2180-2206

Bundschus, Markus; Dejori, Mathaeus; Stetter, Martin; Tresp, Volker; Kriegel, Hans-Peter (2008): Extraction of semantic biomedical relations from text using conditional random fields. In: BMC Bioinformatics 9:207 [PDF, 465kB]

Book Section

Yang, Yinchong; Esteban, Cristóbal; Tresp, Volker (2016): Embedding Mapping Approaches for Tensor Factorization and Knowledge Graph Modelling. In: Sack, Harald (ed.) : The Semantic Web. Latest Advances and New Domains 13th International Conference, ESWC 2016, Heraklion, Crete, Greece, May 29 - June 2, 2016, Proceedings. Theoretical Computer Science and General Issues, Vol. 9678. Cham: Springer. pp. 199-213

Conference or Workshop Item

Esteban, Cristóbal; Staeck, Oliver; Baier, Stephan; Yang, Yinchong; Tresp, Volker (2016): Predicting Clinical Events by Combining Static and Dynamic Information using Recurrent Neural Networks. 2016 IEEE International Conference on Healthcare Informatics (ICHI), 4-7 October 2016, Chicago, Illinois, USA.

Baier, Stephan; Krompass, Denis; Tresp, Volker (2016): Learning Representations for Discrete Sensor Networks using Tensor Decompositions. 2016 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI), 19-21 September 2016, Baden-Baden, Germany.

Esteban, Cristóbal; Tresp, Volker; Yang, Yinchong; Baier, Stephan; Krompaß, Denis (2016): Predicting the Co-Evolution of Event and Knowledge Graphs. 19th International Conference on Information Fusion (FUSION), 5-8 July 2016, Heidelberg, Germany.

This list was generated on Fri Sep 25 00:57:09 2020 CEST.