machine learning – Jörg Simon Wicker

A machine learning damage prediction model for the 2017 Puebla-Morelos, Mexico, earthquake

05/08/202030/07/2020 by Jörg Simon Wicker

Samuel Roeslin, Quincy Ma, Hugon Juárez-Garcia, Alonso Gómez-Bernal, Jörg Wicker, Liam Wotherspoon: A machine learning damage prediction model for the 2017 Puebla-Morelos, Mexico, earthquake. In: Earthquake Spectra, 2020.

A machine learning approach to quantifying the specificity of color-emotion associations and their cultural differences

26/08/2019 by Jörg Simon Wicker

Domicele Jonauskaite, Jörg Wicker, Chrisine Mohr, Nele Dael, Jelena Havelka, Marietta Papadatou-Pastou, Meng Zhang, Daniel Oberfeld : A machine learning approach to quantifying the specificity of color-emotion associations and their cultural differences. In: Royal Society Open Science, 6 (9), pp. 190741, 2019.

What can we learn from the air chemistry of crowds

10/05/2019 by Jörg Simon Wicker

Jonathan Williams, Christof Stönner, Achim Edtbauer, Bettina Derstorff, Efstratios Bourtsoukidis, Thomas Klüpfel, Nicolas Krauter, Jörg Wicker, Stefan Kramer: What can we learn from the air chemistry of crowds?. In: Hansel, Armin; Dunkl, Jürgen (Ed.): 8th International Conference on Proton Transfer Reaction Mass Spectrometry and its Applications, pp. 121-123, Innsbruck University Press, Innsbruck, 2019.

The Best Privacy Defense is a Good Privacy Offense: Obfuscating a Search Engine User’s Profile

06/02/202001/09/2017 by Jörg Simon Wicker

Jörg Wicker, Stefan Kramer: The Best Privacy Defense is a Good Privacy Offense: Obfuscating a Search Engine User's Profile. In: Data Mining and Knowledge Discovery, 31 (5), pp. 1419-1443, 2017, ISSN: 1573-756X.

Eawag-Soil in enviPath: a new resource for exploring regulatory pesticide soil biodegradation pathways and half-life data

06/02/202001/01/2017 by Jörg Simon Wicker

Diogo Latino, Jörg Wicker, Martin Gütlein, Emanuel Schmid, Stefan Kramer, Kathrin Fenner: Eawag-Soil in enviPath: a new resource for exploring regulatory pesticide soil biodegradation pathways and half-life data. In: Environmental Science: Process & Impact, 2017.

Large Classifier Systems in Bio- and Cheminformatics

06/02/202001/01/2013 by Jörg Simon Wicker

Jörg Wicker: Large Classifier Systems in Bio- and Cheminformatics. Technische Universität München, 2013.

Multi-label Classification Using Boolean Matrix Decomposition

06/02/202001/01/2012 by Jörg Simon Wicker

Jörg Wicker, Bernhard Pfahringer, Stefan Kramer: Multi-label Classification Using Boolean Matrix Decomposition. In: Proceedings of the 27th Annual ACM Symposium on Applied Computing, pp. 179–186, ACM, 2012, ISBN: 978-1-4503-0857-1.

Predicting biodegradation products and pathways: a hybrid knowledge- and machine learning-based approach

06/02/202001/01/2010 by Jörg Simon Wicker

Jörg Wicker, Kathrin Fenner, Lynda Ellis, Larry Wackett, Stefan Kramer: Predicting biodegradation products and pathways: a hybrid knowledge- and machine learning-based approach. In: Bioinformatics, 26 (6), pp. 814-821, 2010.

Collaborative development of predictive toxicology applications

06/02/202001/01/2010 by Jörg Simon Wicker

Barry Hardy, Nicki Douglas, Christoph Helma, Micha Rautenberg, Nina Jeliazkova, Vedrin Jeliazkov, Ivelina Nikolova, Romualdo Benigni, Olga Tcheremenskaia, Stefan Kramer, Tobias Girschick, Fabian Buchwald, Jörg Wicker, Andreas Karwath, Martin Gütlein, Andreas Maunz, Haralambos Sarimveis, Georgia Melagraki, Antreas Afantitis, Pantelis Sopasakis, David Gallagher, Vladimir Poroikov, Dmitry Filimonov, Alexey Zakharov, Alexey Lagunin, Tatyana Gloriozova, Sergey Novikov, Natalia Skvortsova, Dmitry Druzhilovsky, Sunil Chawla, Indira Ghosh, Surajit Ray, Hitesh Patel, Sylvia Escher: Collaborative development of predictive toxicology applications. In: Journal of Cheminformatics, 2 (1), pp. 7, 2010, ISSN: 1758-2946.