61 citations · 62 across the 3 of their papers we have counts for
3 papers
Learning the dynamics of nonlinear systems with regional stability guarantees through linear matrix inequality constraints
Daniel Frank, Fahim Shakib, Steffen Staab
This paper presents a method that learns a regionally stable recurrent neural network model from a set of input-output data generated by an unknown dynamical system. Relying on gen…
SCENE: Reasoning about Traffic Scenes using Heterogeneous Graph Neural Networks
Thomas Monninger, Julian Schmidt, Jan Rupprecht +5
Understanding traffic scenes requires considering heterogeneous information about dynamic agents and the static infrastructure. In this work we propose SCENE, a methodology to enco…
Robust Recurrent Neural Network to Identify Ship Motion in Open Water with Performance Guarantees -- Technical Report
Daniel Frank, Decky Aspandi Latif, Michael Muehlebach +2
Recurrent neural networks are capable of learning the dynamics of an unknown nonlinear system purely from input-output measurements. However, the resulting models do not provide an…