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

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, Forthcoming.

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

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.

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What can we learn from the air chemistry of crowds

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.

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

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.

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