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Richard Meyes
Richard Meyes
Bestätigte E-Mail-Adresse bei uni-wuppertal.de
Titel
Zitiert von
Zitiert von
Jahr
Ablation studies in artificial neural networks
R Meyes, M Lu, CW de Puiseau, T Meisen
arXiv preprint arXiv:1901.08644, 2019
2252019
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
892017
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
532019
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
332019
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
252022
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
252020
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
242018
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
162019
Vision transformer in industrial visual inspection
N Hütten, R Meyes, T Meisen
Applied Sciences 12 (23), 11981, 2022
152022
Continuous motion planning for industrial robots based on direct sensory input
R Meyes, C Scheiderer, T Meisen
Procedia CIRP 72, 291-296, 2018
132018
Ablation of a Robot's Brain: Neural Networks Under a Knife
PE Lillian, R Meyes, T Meisen
arXiv preprint arXiv:1812.05687, 2018
92018
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
82021
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
72022
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
52020
Waubert de Puiseau, C. & Meisen, T
R Meyes, M Lu
Ablation studies in artificial neural networks, 2019
52019
Time Series Dataset Survey for Forecasting with Deep Learning
Y Hahn, T Langer, R Meyes, T Meisen
Forecasting 5 (1), 315-335, 2023
42023
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
42021
Transparency and Interpretability for Learned Representations of Artificial Neural Networks
R Meyes
Springer Nature, 2022
22022
Gideon Replay: A library to replay interactions in web-applications
T Langer, R Meyes, T Meisen
SoftwareX 17, 100964, 2022
22022
Artificial intelligence in automotive production
R Meyes, H Tercan, T Meisen
Mobility in a Globalised World 2018, 2019
22019
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