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Moritz Lange
Moritz Lange
PhD Student, Institute for Neural Computation, Ruhr University Bochum
Verified email at ini.rub.de
Title
Cited by
Cited by
Year
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
92021
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
82023
Iterative Oblique Decision Trees Deliver Explainable RL Models
RC Engelhardt, M Oedingen, M Lange, L Wiskott, W Konen
Algorithms 16 (6), 282, 2023
62023
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
52022
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
22024
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
22023
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
22021
Beyond trial and error in reinforcement learning
M Lange, RC Engelhardt, W Konen, L Wiskott
DataNinja sAIOnARA Conference, 2024
12024
Putting the Iterative Training of Decision Trees to the Test on a Real-World Robotic Task
RC Engelhardt, MJ Meinen, M Lange, L Wiskott, W Konen
arXiv preprint arXiv:2412.04974, 2024
2024
Exploring the Reliability of SHAP Values in Reinforcement Learning
RC Engelhardt, M Lange, L Wiskott, W Konen
World Conference on Explainable Artificial Intelligence, 165-184, 2024
2024
Decoding the surface code using graph neural networks
M Lange
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
Graph neural network decoders for stabilizer codes
M Lange, P Havstrom, V Bergentall, K Hammar, O Heuts, B Srivastava, ...
APS March Meeting Abstracts 2023, S72. 009, 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
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