Selection 

L. von Rueden, S. Mayer, K. Beckh, B. Georgiev, S. Giesselbach, R. Heese, B. Kirsch, J. Pfrommer, A. Pick, R. Ramamurthy, M. Walczak, J. Garcke, C. Bauckhage, J. Schuecker, "Informed Machine Learning  A Survey and Taxonomy of Integrating Knowledge into Learning Systems", Preprint at arXiv, 2020 

S. Gramsch, A. Sarishvili, A. Schmeißer, "Analysis of the fiber laydown quality in spunbond processes with simulation experiments evaluated by blocked neural networks", Journal Advances in Polymer Technology, 2020 

C. Bauckhage, R. Sifa, S. Wrobel, "Adiabatic Quantum Computing for MaxSum Diversification", SIAM International Conference on Data Mining (SDM), 2020 

R. Roscher, B. Bohn, M. F. Duarte, J. Garcke, "Explainable Machine Learning for Scientific Insights and Discoveries", IEEE Access, 2020 

F. Jirasek, R. A. S. Alves, J. Damay, R. A. Vandermeulen, R. Bamler, M. Bortz, S. Mandt, M. Kloft, H. Hasse, "Machine Learning in Thermodynamics: Prediction of Activity Coefficients by Matrix Completion", The Journal of Physical Chemistry Letters, 2020 

T. Emter, A. Schirg, P. Woock, J. Petereit, "Stochastic Cloning for Robust Fusion of Multiple Relative and Absolute Measurements", IEEE Intelligent Vehicles Symposium (IV), 2019 

C. Bauckhage, R. Sifa, T. Dong, "Prototypes within Minimum Enclosing Balls", International Conference on Artificial Neural Networks, 2019 

A. Diedrich, A. Maier, O. Niggemann, "Modelbased Diagnosis of Hybrid Systems Using Satisfiability Modulo Theory", Proc. AAAI, 2019 

B. Bohn, M. Griebel, C. Rieger, "A Representer Theorem for Deep Kernel Learning", ournal of Machine Learning Research, 2019 

M. Fullen, A. Maier, A. Nazarenko, V. Aksu, S. Jenderny, C. Röcker, "Machine learning for assistance systems: Patternbased approach to online step recognition", INDIN  International Conference on Industrial Informatics, 2019 

Ali, M., Hoyt, C. T., DomingoFernández, D., & Lehman, J., "Predicting Missing Links Using PyKEEN", International Conference on the Semantic Web, 2019 

L. von Rueden, S. Mayer, J. Garcke, C. Bauckhage J. Schuecker, "Informed Machine LearningTowards a Taxonomy of Explicit Integration of Knowledge into Machine Learning", arXiv 1903.12394, 2019 

A. Diedrich, A. Maier, and O. Niggemann, "Modelbased Diagnosis pf Hybrid Systems Using Satisfiability Modulo Theory", Proc. AAAI, 2019 

J. Schuecker, S. Goedeke, and M. Helias, "Optimal Sequence Memory in Driven Random Network"s, Physical Review X, 8(4), 2018 

R. Sifa, D. Paurat, D. Trabold, and C. Bauckhage, "Simple Recurrent Neural Networks for Support Vector Machine Training", Proc. ICANN, 2018 

R. Ramamurthy, C. Bauckhage, R. Sifa, and S. Wrobel, "Policy Learning Using SPSA", Proc. ICANN, 2018 

B. Wulff, J. Schuecker, and C. Bauckhage, "SPSA for LayerWise Training of Deep Networks", Proc. ICANN, 2018 

R. Sifa, "An overview of FrankWolfe optimization for stochasticity constrained interpretable matrix and tensor factorization", Proc. ICANN, 2018 

C. Bauckhage, "A Neural Network Implementation of FrankWolfe Optimization", Proc. Int. Conf. on Artificial Neural Networks, 2017 

M. Griebel, C. Rieger, "Reproducing Kernel Hilbert Spaces for Parametric Partial Differential Equations", SIAM/ASA Journal on Uncertainty Quantification, vol. 5, 2017 

B. Bohn, J. Garcke, M. Griebel, "A Sparse Grid Based Method for Generative Dimensionality Reduction of Highdimensional Data", Journal of Computational Physics, vol. 309, 2016 

A. Kuwertz, J. Beyerer, "Extending Adaptive World Modeling by Identifying and Handling Insufficient Knowledge Models", Journal of Applied Logic, vol. 19, no. 2, 2016 

P. Li, O. Niggemann, "Improving Clustering Based Anomaly Detection with Concave Hull: An Application in Condition Monitoring of Wind Turbines", in Proc. IEEE Conf. on Industrial Informatics, 2016. 

M. Neumann, R. Garnett, C. Bauckhage, K. Kersting, "Propagation Kernels: Efficient Graph Kernels from Propagated Information" Machine Learning, vol. 10, no. 2, 2016 

M. Bortz, V. Maag, J. Schwientk, R. Benfer, R. Böttcher, J. Burger, E. von Harbou, N. Asprion, K.H. Küfer, H. Hasse, "Decision Support by Multicriteria Optimization in Process Development: An Integrated Approach for Robust Planning and Design of Plant Experiments", Computer Aided Chemical Engineering, vol. 37, 2015 

S. Zhang, C. Bauckhage, A. Cremers, "Informed Haarlike Features Improve Pedestrian Detection", in Proc. IEEE CVPR, 2014 
