| Informed Machine Learning - A Taxonomy and Survey of Integrating Prior Knowledge into Learning Systems L von Rueden, S Mayer, K Beckh, B Georgiev, S Giesselbach, R Heese, ... IEEE Transactions on Knowledge and Data Engineering, 2021 | 628 | 2021 |
| Combining machine learning and simulation to a hybrid modelling approach: Current and future directions L von Rueden, S Mayer, R Sifa, C Bauckhage, J Garcke Advances in Intelligent Data Analysis XVIII: 18th International Symposium on …, 2020 | 174 | 2020 |
| Informed machine learning - Towards a taxonomy of explicit integration of knowledge into machine learning L von Rueden, S Mayer, J Garcke, C Bauckhage, J Schuecker arXiv preprint arXiv:1903.12394, 2019 | 81* | 2019 |
| Magnostics: Image-based search of interesting matrix views for guided network exploration M Behrisch, B Bach, M Hund, M Delz, L Von Rüden, JD Fekete, T Schreck IEEE Transactions on Visualization and Computer Graphics 23 (1), 31-40, 2016 | 42 | 2016 |
| Explainable machine learning with prior knowledge: an overview K Beckh, S Müller, M Jakobs, V Toborek, H Tan, R Fischer, P Welke, ... arXiv preprint arXiv:2105.10172, 2021 | 33 | 2021 |
| Harnessing prior knowledge for explainable machine learning: An overview K Beckh, S Müller, M Jakobs, V Toborek, H Tan, R Fischer, P Welke, ... 2023 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML), 450-463, 2023 | 11 | 2023 |
| Informed pre-training on prior knowledge L von Rueden, S Houben, K Cvejoski, C Bauckhage, N Piatkowski arXiv preprint arXiv:2205.11433, 2022 | 10 | 2022 |
| Knowledge augmented machine learning with applications in autonomous driving: A survey J Wörmann, D Bogdoll, E Bührle, H Chen, EF Chuo, K Cvejoski, L van Elst, ... arXiv preprint arXiv:2205.04712, 2022 | 10 | 2022 |
| Street-map based validation of semantic segmentation in autonomous driving L von Rueden, T Wirtz, F Hueger, JD Schneider, N Piatkowski, ... 2020 25th International Conference on Pattern Recognition (ICPR), 10203-10210, 2021 | 8 | 2021 |
| Towards Intelligent Food Waste Prevention: An Approach Using Scalable and Flexible Harvest Schedule Optimization With Evolutionary Algorithms M Günder, N Piatkowski, L Von Rueden, R Sifa, C Bauckhage IEEE Access 9, 169044-169055, 2021 | 4 | 2021 |
| Separating the wheat from the chaff: Identifying relevant and similar performance data with visual analytics L von Rüden, MA Hermanns, M Behrisch, D Keim, B Mohr, F Wolf Workshop on Visual Performance Analysis (VPA), Supercomputing Conference, 2015 | 4 | 2015 |
| How Does Knowledge Injection Help in Informed Machine Learning? L von Rueden, J Garcke, C Bauckhage 2023 International Joint Conference on Neural Networks (IJCNN), 1-8, 2023 | 1 | 2023 |
| Evolutionary Hierarchical Harvest Schedule Optimization for Food Waste Prevention M Günder, N Piatkowski, L von Rueden, R Sifa, C Bauckhage arXiv preprint arXiv:2112.10712, 2021 | 1 | 2021 |
| Towards Map-Based Validation of Semantic Segmentation Masks L von Rueden, T Wirtz, F Hueger, JD Schneider, C Bauckhage Workshop on AI for Autonomous Driving (AIAD), International Conference on …, 2020 | 1 | 2020 |
| Informed Machine Learning: Integrating Prior Knowledge into Data-Driven Learning Systems L von Rüden Universitäts-und Landesbibliothek Bonn, 2023 | | 2023 |
Christian BauckhageProf. of Computer Science, University of Bonn, Fraunhofer IAISDirección de correo verificada de bit.uni-bonn.de
