21 citations · 69 across the 10 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…
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…
How Training Data Impacts Performance in Learning-based Control
Armin Lederer, Alexandre Capone, Jonas Umlauft +1
When first principle models cannot be derived due to the complexity of the real system, data-driven methods allow us to build models from system observations. As these models are e…
Data selection for multi-task learning under dynamic constraints
Alexandre Capone, Armin Lederer, Jonas Umlauft +1
Learning-based techniques are increasingly effective at controlling complex systems using data-driven models. However, most work done so far has focused on learning individual task…