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02/23/2023
Sharp Calibrated Gaussian Processes
While Gaussian processes are a mainstay for various engineering and scie...
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06/28/2022
Dext-Gen: Dexterous Grasping in Sparse Reward Environments with Full Orientation Control
Reinforcement learning is a promising method for robotic grasping as it ...
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12/10/2021
Structure-Preserving Learning Using Gaussian Processes and Variational Integrators
Gaussian process regression is often applied for learning unknown system...
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09/06/2021
Gaussian Process Uniform Error Bounds with Unknown Hyperparameters for Safety-Critical Applications
Gaussian processes have become a promising tool for various safety-criti...
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05/25/2021
Gaussian Process-based Stochastic Model Predictive Control for Overtaking in Autonomous Racing
A fundamental aspect of racing is overtaking other race cars. Whereas pr...
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11/20/2020
The Value of Data in Learning-Based Control for Training Subset Selection
Despite the existence of formal guarantees for learning-based control ap...
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07/24/2020
Anticipating the Long-Term Effect of Online Learning in Control
Control schemes that learn using measurement data collected online are i...
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05/25/2020
How Training Data Impacts Performance in Learning-based Control
When first principle models cannot be derived due to the complexity of t...
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05/04/2020