P. Santana Chacon, M. Hammer, I. Wochner, J. Walter, and S. Schmitt. Software, (2023)Related to: P. F. S. Chacon, M. Hammer, I. Wochner, J. R. Walter and S. Schmitt. A physiologically enhanced muscle spindle model: using a Hill-type model for extrafusal fibers as template for intrafusal fibers. doi: 10.1080/10255842.2023.2293652.
I. Wochner, and S. Schmitt. Software, (2022)Related to: Wochner, I., Schumacher, P., Martius, G., Büchler, D., Schmitt, S., & Haeufle, D. F. (2022). Learning with Muscles: Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks. Conference on Robot Learning (CoRL) 2022. url: https://openreview.net/forum?id=Xo3eOibXCQ8.
V. Wagner, S. Höpfl, V. Klingel, M. Pop, and N. Radde. IFAC-PapersOnLine, 55 (23):
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M. Millard, F. Kempter, N. Stutzig, T. Siebert, and J. Fehr. Proceedings of the International Research Council on the Biomechanics of Injury Conference, IRC-23-334, Cambridge, UK, (2023)accepted for publication.
J. Kneifl, J. Hay, and J. Fehr. Software, (2022)Related to: Jonas Kneifl, Julian Hay, and Jörg Fehr (2021). Real-time Human Response Prediction Using a Non-intrusive Data-driven Model Reduction Scheme. Preprint. arXiv: 2110.13583 [math.DS].
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