| Pytorch geometric temporal: Spatiotemporal signal processing with neural machine learning models B Rozemberczki, P Scherer, Y He, G Panagopoulos, A Riedel, ... Proceedings of the 30th ACM International Conference on Information …, 2021 | 75 | 2021 |
| A deep learning-based worker assistance system for error prevention: case study in a real-world manual assembly A Riedel, J Gerlach, M Dietsch, S Herbst, F Engelmann, N Brehm, ... Advances in Production Engineering & Management 16 (4), 393-404, 2021 | 6 | 2021 |
| A beta-glucosidase of an insect herbivore determines both toxicity and deterrence of a dandelion defense metabolite M Huber, T Roder, S Irmisch, A Riedel, S Gablenz, J Fricke, P Rahfeld, ... Elife 10, e68642, 2021 | 4 | 2021 |
| Hand gesture recognition of methods-time measurement-1 motions in manual assembly tasks using graph convolutional networks A Riedel, N Brehm, T Pfeifroth Applied Artificial Intelligence 36 (1), 2014191, 2022 | 3 | 2022 |
| Bag of Tricks for Training Brain-Like Deep Neural Networks A Riedel Computational and Systems Neuroscience (COSYNE) 2022, Brain-Score Workshop, 2022 | 2 | 2022 |
| Adapting Brain-Like Neural Networks for Modeling Cortical Visual Prostheses J Granley, A Riedel, M Beyeler SVRHM 2022 Workshop@ NeurIPS, 2022 | | 2022 |
| Adapting Brain-Like Neural Networks for Modeling Cortical Visual Prostheses J Granley, A Riedel, M Beyeler arXiv preprint arXiv:2209.13561, 2022 | | 2022 |
| Montagegerechte Gestaltungsrichtlinien unter Anwendung von Objekterkennungsalgorithmen J Gerlach, A Riedel, S Uslu, F Engelmann, N Brehm 21. Nachwuchswissenschaftler* innenkonferenz, 151, 2021 | | 2021 |
| Montagegerechte Gestaltungsrichtlinien mittels Deep Learning J Gerlach, A Riedel, S Uslu, F Engelmann, N Brehm | | 2021 |
