| Physics-informed neural networks-based model predictive control for multi-link manipulators J Nicodemus, J Kneifl, J Fehr, B Unger IFAC-PapersOnLine 55 (20), 331-336, 2022 | 48 | 2022 |
| A non-intrusive nonlinear model reduction method for structural dynamical problems based on machine learning J Kneifl, D Grunert, J Fehr | 21 | 2020 |
| Low-dimensional data-based surrogate model of a continuum-mechanical musculoskeletal system based on non-intrusive model order reduction J Kneifl, D Rosin, O Avci, O Röhrle, J Fehr Archive of Applied Mechanics 93 (9), 3637-3663, 2023 | 15 | 2023 |
| Real-time human response prediction using a non-intrusive data-driven model reduction scheme J Kneifl, J Hay, J Fehr IFAC-PapersOnLine 55 (20), 283-288, 2022 | 4 | 2022 |
| VENI, VINDy, VICI: a variational reduced-order modeling framework with uncertainty quantification P Conti, J Kneifl, A Manzoni, A Frangi, J Fehr, SL Brunton, JN Kutz arXiv preprint arXiv:2405.20905, 2024 | 3 | 2024 |
| Multi-hierarchical surrogate learning for explicit structural dynamical systems using graph convolutional neural networks J Kneifl, J Fehr, SL Brunton, JN Kutz Computational Mechanics, 1-21, 2024 | 2* | 2024 |
| On using machine learning algorithms for motorcycle collision detection P Rodegast, S Maier, J Kneifl, J Fehr Discover Applied Sciences 6 (6), 326, 2024 | 1 | 2024 |
| Simulation data from motorcycle sensors in operational and crash scenarios P Rodegast, S Maier, J Kneifl, J Fehr DaRUS, 2023 | 1 | 2023 |
| Machine Learning Algorithms for Learning Nonlinear Terms of Reduced Mechanical Models in Explicit Structural Dynamics J Kneifl, J Fehr PAMM 20 (S1), e202000353, 2021 | 1 | 2021 |
| ApHIN-Autoencoder-based port-Hamiltonian Identification Networks (Software Package) J Kneifl, J Rettberg, J Herb DaRUS, 2024 | | 2024 |
| Data-driven identification of latent port-Hamiltonian systems J Rettberg, J Kneifl, J Herb, P Buchfink, J Fehr, B Haasdonk arXiv preprint arXiv:2408.08185, 2024 | | 2024 |
| An improved development process of production plants using digital twins with extended dynamic behaviour in virtual commissioning and control–Simulation@ Operations D Pfeifer, J Scheid, J Kneifl, J Fehr PAMM 23 (3), e202300225, 2023 | | 2023 |
| Human Occupant Motion in Pre-Crash Scenario J Kneifl, J Hay, J Fehr DaRUS, 2022 | | 2022 |
| Low-Dimensional Identification of Port-Hamiltonian Systems by Combining Model Order Reduction and Machine Learning J Rettberg, J Kneifl, J Fehr, B Haasdonk | | |
Jörg FehrProfessor at Institute of Engineering and Computational Mechanics and SimTech, University ofBestätigte E-Mail-Adresse bei itm.uni-stuttgart.de
