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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A Hybrid Machine Learning and Knowledge Based Approach to Limit Combinatorial Explosion in Biodegradation Prediction

Jörg Wicker, Kathrin Fenner, Stefan Kramer: A Hybrid Machine Learning and Knowledge Based Approach to Limit Combinatorial Explosion in Biodegradation Prediction. In: Lässig, Jörg; Kersting, Kristian; Morik, Katharina (Ed.): Computational Sustainability, pp. 75-97, Springer International Publishing, Cham, 2016, ISBN: 978-3-319-31858-5.

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A Nonlinear Label Compression and Transformation Method for Multi-Label Classification using Autoencoders

Jörg Wicker, Andrey Tyukin, Stefan Kramer: A Nonlinear Label Compression and Transformation Method for Multi-Label Classification using Autoencoders. In: Bailey, James; Khan, Latifur; Washio, Takashi; Dobbie, Gill; Huang, Zhexue Joshua; Wang, Ruili (Ed.): The 20th Pacific Asia Conference on Knowledge Discovery and Data Mining (PAKDD), pp. 328-340, Springer International Publishing, Switzerland, 2016, ISBN: 978-3-319-31753-3.

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Cinema audiences reproducibly vary the chemical composition of air during films, by broadcasting scene specific emissions on breath

Jonathan Williams, Christof Stönner, Jörg Wicker, Nicolas Krauter, Bettina Derstorff, Efstratios Bourtsoukidis, Thomas Klüpfel, Stefan Kramer: Cinema audiences reproducibly vary the chemical composition of air during films, by broadcasting scene specific emissions on breath. In: Scientific Reports, 6 , 2016.

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Cinema Data Mining: The Smell of Fear

Jörg Wicker, Nicolas Krauter, Bettina Derstorff, Christof Stönner, Efstratios Bourtsoukidis, Thomas Klüpfel, Jonathan Williams, Stefan Kramer: Cinema Data Mining: The Smell of Fear. In: Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1235-1304, ACM ACM, New York, NY, USA, 2015, ISBN: 978-1-4503-3664-2.

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Scavenger – A Framework for the Efficient Evaluation of Dynamic and Modular Algorithms

Andrey Tyukin, Stefan Kramer, Jörg Wicker : Scavenger - A Framework for the Efficient Evaluation of Dynamic and Modular Algorithms. In: Bifet, Albert; May, Michael; Zadrozny, Bianca; Gavalda, Ricard; Pedreschi, Dino; Cardoso, Jaime; Spiliopoulou, Myra (Ed.): Machine Learning and Knowledge Discovery in Databases, pp. 325-328, Springer International Publishing, 2015, ISBN: 978-3-319-23460-1.

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