152 citations · 285 across the 20 of their papers we have counts for
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The Impact of Data on the Stability of Learning-Based Control- Extended Version
Armin Lederer, Alexandre Capone, Thomas Beckers +2
Despite the existence of formal guarantees for learning-based control approaches, the relationship between data and control performance is still poorly understood. In this paper, w…
Deep Learning based Uncertainty Decomposition for Real-time Control
Neha Das, Jonas Umlauft, Armin Lederer +2
Data-driven control in unknown environments requires a clear understanding of the involved uncertainties for ensuring safety and efficient exploration. While aleatoric uncertainty…
Online learning-based trajectory tracking for underactuated vehicles with uncertain dynamics
Thomas Beckers, Leonardo Colombo, Sandra Hirche +1
Underactuated vehicles have gained much attention in the recent years due to the increasing amount of aerial and underwater vehicles as well as nanosatellites. Trajectory tracking…
Localized active learning of Gaussian process state space models
Alexandre Capone, Jonas Umlauft, Thomas Beckers +2
The performance of learning-based control techniques crucially depends on how effectively the system is explored. While most exploration techniques aim to achieve a globally accura…
Prediction with Approximated Gaussian Process Dynamical Models
Thomas Beckers, Sandra Hirche
The modeling and simulation of dynamical systems is a necessary step for many control approaches. Using classical, parameter-based techniques for modeling of modern systems, e.g.,…