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Carl Julius Martensen
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Universal differential equations for scientific machine learning
C Rackauckas, Y Ma, J Martensen, C Warner, K Zubov, R Supekar, ...
arXiv preprint arXiv:2001.04385, 2020
6402020
Universal differential equations for scientific machine learning. arXiv
C Rackauckas, Y Ma, J Martensen, C Warner, K Zubov, R Supekar, ...
arXiv preprint arXiv:2001.04385, 2020
282020
Universal differential equations for scientific machine learning. arXiv 2020
C Rackauckas, Y Ma, J Martensen, C Warner, K Zubov, R Supekar, ...
arXiv preprint arXiv:2001.04385, 2001
202001
Model Simplification For Dynamic Control of Series-Parallel Hybrid Robots - A Representative Study on the Effects of Neglected Dynamics
FK Shivesh Kumar, Julius Martensen, Andreas Mueller
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS-2019), 2019
92019
Selection of decoupling control methods suited for automated design for uncertain TITO processes
M Noeding, J Martensen, N Lemke, W Tegethoff, J Koehler
2018 IEEE 14th International Conference on Control and Automation (ICCA …, 2018
92018
Universal differential equations for scientific machine learning. arXiv preprint 2020
C Rackauckas, Y Ma, J Martensen, C Warner, K Zubov, R Supekar, ...
arXiv preprint arXiv:2001.04385, 2001
72001
Universal differential equations for scientific machine learning, arXiv preprint
C Rackauckas, Y Ma, J Martensen, C Warner, K Zubov, R Supekar, ...
arXiv preprint arXiv:2001.04385 10, 0
4
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