| Machine-learning models to replicate large-eddy simulations of air pollutant concentrations along boulevard-type streets M Lange, H Suominen, M Kurppa, L Järvi, E Oikarinen, R Savvides, ... Geoscientific Model Development 14 (12), 7411-7424, 2021 | 6 | 2021 |
| Iterative Oblique Decision Trees Deliver Explainable RL Models RC Engelhardt, M Oedingen, M Lange, L Wiskott, W Konen Algorithms 16 (6), 282, 2023 | 2 | 2023 |
| Sample-Based Rule Extraction for Explainable Reinforcement Learning RC Engelhardt, M Lange, L Wiskott, W Konen International Conference on Machine Learning, Optimization, and Data Science …, 2022 | 2 | 2022 |
| Shedding light into the black box of Reinforcement Learning R Engelhardt, M Lange, L Wiskott, W Konen Proceedings of the workshop “trustworthy AI in the wild”, kl2021 held at …, 2021 | 2 | 2021 |
| Improving Reinforcement Learning Efficiency with Auxiliary Tasks in Non-visual Environments: A Comparison M Lange, N Krystiniak, RC Engelhardt, W Konen, L Wiskott International Conference on Machine Learning, Optimization, and Data Science …, 2023 | 1 | 2023 |
| Interpretable Brain-Inspired Representations Improve RL Performance on Visual Navigation Tasks M Lange, RC Engelhardt, W Konen, L Wiskott arXiv preprint arXiv:2402.12067, 2024 | | 2024 |
| Benchmarks for Physical Reasoning AI A Melnik, R Schiewer, M Lange, A Muresanu, M Saeidi, A Garg, H Ritter arXiv preprint arXiv:2312.10728, 2023 | | 2023 |
| Ökolopoly: Case Study on Large Action Spaces in Reinforcement Learning RC Engelhardt, R Raycheva, M Lange, L Wiskott, W Konen International Conference on Machine Learning, Optimization, and Data Science …, 2023 | | 2023 |
| Distribution Matching–Semi-Supervised Feature Selection for Biased Labelled Data MJ Lange, S Chandramouli Helsingin yliopisto, 2020 | | 2020 |
| Finding the Relevant Samples for Decision Trees in Reinforcement Learning RC Engelhardt, M Lange, L Wiskott, W Konen | | |
Laurenz WiskottProfessor of Theory of Neural Systems, Institut für Neuroinformatik, Ruhr-Universität BochumVerified email at ini.rub.de
