Ablation studies in artificial neural networks R Meyes, M Lu, CW de Puiseau, T Meisen arXiv preprint arXiv:1901.08644, 2019 | 234 | 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 | 91 | 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 | 55 | 2019 |
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 | 34 | 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 | 27 | 2022 |
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 | 25 | 2020 |
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 | 25 | 2018 |
Vision transformer in industrial visual inspection N Hütten, R Meyes, T Meisen Applied Sciences 12 (23), 11981, 2022 | 17 | 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 | 17 | 2019 |
Continuous motion planning for industrial robots based on direct sensory input R Meyes, C Scheiderer, T Meisen Procedia CIRP 72, 291-296, 2018 | 14 | 2018 |
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 |
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 | 8 | 2022 |
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 | 8 | 2021 |
Time Series Dataset Survey for Forecasting with Deep Learning Y Hahn, T Langer, R Meyes, T Meisen Forecasting 5 (1), 315-335, 2023 | 7 | 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 |
Waubert de Puiseau, C. & Meisen, T R Meyes, M Lu Ablation studies in artificial neural networks, 2019 | 5 | 2019 |
Transparency and Interpretability for Learned Representations of Artificial Neural Networks R Meyes Springer Nature, 2022 | 2 | 2022 |
Gideon Replay: A library to replay interactions in web-applications T Langer, R Meyes, T Meisen SoftwareX 17, 100964, 2022 | 2 | 2022 |
Artificial intelligence in automotive production R Meyes, H Tercan, T Meisen Mobility in a Globalised World 2018, 2019 | 2 | 2019 |