Laura von Rueden
Laura von Rueden
Research Scientist, Fraunhofer IAIS, Fraunhofer Center for Machine Learning
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Cited by
Cited by
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
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
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
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
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
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
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
Informed pre-training on prior knowledge
L von Rueden, S Houben, K Cvejoski, C Bauckhage, N Piatkowski
arXiv preprint arXiv:2205.11433, 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
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
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
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
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
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
Informed Machine Learning: Integrating Prior Knowledge into Data-Driven Learning Systems.
L von Rüden
Universitäts-und Landesbibliothek Bonn, 2023
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