NeuralODEs lead to amazing results in academic examples. But the expectations are often being disappointed as soon as one tries to adapt this concept for real engineering use cases. Bad convergence behavior, handling of discontinuities and/or instabilities are just some of the stumbling blocks that might pop up during the first steps. During the UPSIM project runtime, we have been researching how to tackle these challenges and integrate real life industrial models in NeuralODEs using FMI. A summary of the methods developed was presented at the JuliaCon 2023 at MIT Boston – at an challenging application from automotive engineering.
Check out the workshop held by our colleagues Tobias Thummerer and Lars Mikelsons from University of Augsburg. You can access the slides here.
