| Ablation studies in artificial neural networks R Meyes, M Lu, CW de Puiseau, T Meisen arXiv preprint arXiv:1901.08644, 2019 | 332 | 2019 |
| Motion planning for industrial robots using reinforcement learning R Meyes, H Tercan, S Roggendorf, T Thiele, C Büscher, M Obdenbusch, ... Procedia CIRP 63, 107-112, 2017 | 104 | 2017 |
| Multi-agent reinforcement learning for job shop scheduling in flexible manufacturing systems S Baer, J Bakakeu, R Meyes, T Meisen 2019 Second International Conference on Artificial Intelligence for …, 2019 | 66 | 2019 |
| On reliability of reinforcement learning based production scheduling systems: a comparative survey C Waubert de Puiseau, R Meyes, T Meisen Journal of Intelligent Manufacturing 33 (4), 911-927, 2022 | 48 | 2022 |
| A recurrent neural network architecture for failure prediction in deep drawing sensory time series data R Meyes, J Donauer, A Schmeing, T Meisen Procedia Manufacturing 34, 789-797, 2019 | 42 | 2019 |
| Interdisciplinary data driven production process analysis for the internet of production R Meyes, H Tercan, T Thiele, A Krämer, J Heinisch, M Liebenberg, G Hirt, ... Procedia Manufacturing 26, 1065-1076, 2018 | 31 | 2018 |
| Under the hood of neural networks: Characterizing learned representations by functional neuron populations and network ablations R Meyes, CW de Puiseau, A Posada-Moreno, T Meisen arXiv preprint arXiv:2004.01254, 2020 | 28 | 2020 |
| Vision transformer in industrial visual inspection N Hütten, R Meyes, T Meisen Applied Sciences 12 (23), 11981, 2022 | 21 | 2022 |
| Ablation studies to uncover structure of learned representations in artificial neural networks R Meyes, M Lu, CW de Puiseau, T Meisen Proceedings on the International Conference on Artificial Intelligence (ICAI …, 2019 | 20 | 2019 |
| Deep Learning for Automated Visual Inspection in Manufacturing and Maintenance: A Survey of Open-Access Papers N Hütten, M Alves Gomes, F Hölken, K Andricevic, R Meyes, T Meisen Applied System Innovation 7 (1), 11, 2024 | 19 | 2024 |
| Time series dataset survey for forecasting with deep learning Y Hahn, T Langer, R Meyes, T Meisen Forecasting 5 (1), 315-335, 2023 | 18 | 2023 |
| Will this online shopping session succeed? predicting customer's purchase intention using embeddings M Alves Gomes, R Meyes, P Meisen, T Meisen Proceedings of the 31st ACM international conference on information …, 2022 | 15 | 2022 |
| Continuous motion planning for industrial robots based on direct sensory input R Meyes, C Scheiderer, T Meisen Procedia CIRP 72, 291-296, 2018 | 15 | 2018 |
| Discovering heuristics and metaheuristics for job shop scheduling from scratch via deep reinforcement learning T Van Ekeris, R Meyes, T Meisen ESSN: 2701-6277, 2021 | 13 | 2021 |
| Ablation of a Robot's Brain: Neural Networks Under a Knife PE Lillian, R Meyes, T Meisen arXiv preprint arXiv:1812.05687, 2018 | 9 | 2018 |
| Transparent and Interpretable State of Health Forecasting of Lithium‐Ion Batteries with Deep Learning and Saliency Maps F von Bülow, Y Hahn, R Meyes, T Meisen International Journal of Energy Research 2023 (1), 9922475, 2023 | 6 | 2023 |
| Transparent and interpretable failure prediction of sensor time series data with convolutional neural networks R Meyes, N Hütten, T Meisen Procedia CIRP 104, 1446-1451, 2021 | 5 | 2021 |
| How do you act? an empirical study to understand behavior of deep reinforcement learning agents R Meyes, M Schneider, T Meisen arXiv preprint arXiv:2004.03237, 2020 | 5 | 2020 |
| Transparency and Interpretability for Learned Representations of Artificial Neural Networks R Meyes Springer Nature, 2022 | 3 | 2022 |
| Researchers’ Concerns on Artificial Intelligence Ethics: Results from a Scenario-Based Survey M Jantunen, R Meyes, V Kurchyna, T Meisen, P Abrahamsson, ... Proceedings of the 7th ACM/IEEE International Workshop on Software-intensive …, 2024 | 2 | 2024 |
Tobias MeisenBergische Universität Wuppertal, previously RWTH Aachen UniversityDirección de correo verificada de uni-wuppertal.de