2 papers
cs.LG2025
Learning Geometrically-Informed Lyapunov Functions with Deep Diffeomorphic RBF Networks
Samuel Tesfazgi, Leonhard Sprandl, Sandra Hirche
The practical deployment of learning-based autonomous systems would greatly benefit from tools that flexibly obtain safety guarantees in the form of certificate functions from data…
eess.SY2024
Stable Inverse Reinforcement Learning: Policies from Control Lyapunov Landscapes
Samuel Tesfazgi, Leonhard Sprandl, Armin Lederer +1
Learning from expert demonstrations to flexibly program an autonomous system with complex behaviors or to predict an agent's behavior is a powerful tool, especially in collaborativ…