| Ablation studies in artificial neural networks R Meyes, M Lu, CW de Puiseau, T Meisen arXiv preprint arXiv:1901.08644, 2019 | 225 | 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 | 26 | 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 |
| 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 |
| Ablation studies in artificial neural networks. arXiv 2019 R Meyes, M Lu, CW de Puiseau, T Meisen arXiv preprint arXiv:1901.08644, 1901 | 17 | 1901 |
| Dynamic Storage Location Assignment in Warehouses Using Deep Reinforcement Learning C Waubert de Puiseau, DT Nanfack, H Tercan, J Löbbert-Plattfaut, ... Technologies 10 (6), 129, 2022 | 9 | 2022 |
| schlably: A Python framework for deep reinforcement learning based scheduling experiments CW de Puiseau, J Peters, C Dörpelkus, H Tercan, T Meisen SoftwareX 22, 101383, 2023 | 3 | 2023 |
| Reducing the Sim2Real-gap in extrusion blow molding using random forest regressors RF Maack, CW de Puiseau, A Sokolova, H Atsbha, H Tercan, T Meisen Manufacturing Letters 33, 843-849, 2022 | 1 | 2022 |
| On The Effectiveness Of Bottleneck Information For Solving Job Shop Scheduling Problems Using Deep Reinforcement Learning C Waubert de Puiseau, L Zey, M Demir, H Tercan, T Meisen ESSN: 2701-6277, 738-749, 2023 | | 2023 |
| Curriculum Learning in Job Shop Scheduling using Reinforcement Learning C Waubert de Puiseau, H Tercan, T Meisen Proceedings of the Conference on Production Systems and Logistics: CPSL 2023 …, 2023 | | 2023 |
