16 citations · 18 across the 3 of their papers we have counts for
3 papers
cs.LG2023★ 16 cited
Low-dimensional Data-based Surrogate Model of a Continuum-mechanical Musculoskeletal System Based on Non-intrusive Model Order Reduction
Jonas Kneifl, David Rosin, Oliver Röhrle +1
In recent decades, the main focus of computer modeling has been on supporting the design and development of engineering prototyes, but it is now ubiquitous in non-traditional areas…
math.DS2021
Real-time Human Response Prediction Using a Non-intrusive Data-driven Model Reduction Scheme
Jonas Kneifl, Julian Hay, Jörg Fehr
Recent research in non-intrusive data-driven model order reduction (MOR) enabled accurate and efficient approximation of parameterized ordinary differential equations (ODEs). Howev…
math.OC2021★ 2 cited
Physics-informed Neural Networks-based Model Predictive Control for Multi-link Manipulators
Jonas Nicodemus, Jonas Kneifl, Jörg Fehr +1
We discuss nonlinear model predictive control (NMPC) for multi-body dynamics via physics-informed machine learning methods. Physics-informed neural networks (PINNs) are a promising…