publications

A comprehensive comparison of molecular feature representations for use in predictive modeling

13/01/2021 by Jörg Simon Wicker

Tomaž Stepišnik, Blaž Škrlj, Jörg Wicker, Dragi Kocev: A comprehensive comparison of molecular feature representations for use in predictive modeling. In: Computers in Biology and Medicine, 130 , pp. 104197, 2021, ISSN: 0010-4825.

Balancing Utility and Fairness against Privacy in Medical Data

28/09/2020 by Jörg Simon Wicker

Andrew Chester, Yun Sing Koh, Jörg Wicker, Quan Sun, Junjae Lee: Balancing Utility and Fairness against Privacy in Medical Data. In: IEEE Symposium Series on Computational Intelligence (SSCI), pp. 1226-1233, IEEE, 2020.

Feature Engineering for a Seismic Loss Prediction Model using Machine Learning, Christchurch Experience

24/02/202117/09/2020 by Jörg Simon Wicker

Samuel Roeslin, Quincy Ma, and Pavan Chigullapally, Jörg Wicker, Liam Wotherspoon: Feature Engineering for a Seismic Loss Prediction Model using Machine Learning, Christchurch Experience. In: 17th World Conference on Earthquake Engineering, 2020.

Your Best Guess When You Know Nothing: Identification and Mitigation of Selection Bias

25/08/202024/08/2020 by Jörg Simon Wicker

Katharina Dost, Katerina Taskova, Pat Riddle, Jörg Wicker: Your Best Guess When You Know Nothing: Identification and Mitigation of Selection Bias. In: 2020 IEEE International Conference on Data Mining (ICDM), pp. 996-1001, IEEE, 2020, ISSN: 2374-8486.

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, 36 (2), pp. 314-339, 2020.

XOR-based Boolean Matrix Decomposition

06/02/202008/11/2019 by Jörg Simon Wicker

Jörg Wicker, Yan Cathy Hua, Rayner Rebello, Bernhard Pfahringer: XOR-based Boolean Matrix Decomposition. In: Wang, Jianyong; Shim, Kyuseok; Wu, Xindong (Ed.): 2019 IEEE International Conference on Data Mining (ICDM), pp. 638-647, IEEE, 2019, ISBN: 978-1-7281-4604-1.

Data integration for the development of a seismic loss prediction model for residential buildings in New Zealand

12/10/201920/09/2019 by Jörg Simon Wicker

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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.

Proof of concept study: Testing human volatile organic compounds as tools for age classification of films

11/10/2018 by Jörg Simon Wicker

Christof Stönner, Achim Edtbauer, Bettina Derstorff, Efstratios Bourtsoukidis, Thomas Klüpfel, Jörg Wicker, Jonathan Williams: Proof of concept study: Testing human volatile organic compounds as tools for age classification of films. In: PLOS One, 13 (10), pp. 1-14, 2018.