Search Results for author:
Found 4 papers, 1 papers with code
Convolutional Neural Networks as 2-D systems
This paper introduces a novel representation of convolutional Neural Networks (CNNs) in terms of 2-D dynamical systems.
Learning-enhanced robust controller synthesis with rigorous statistical and control-theoretic guarantees
The combination of machine learning with control offers many opportunities, in particular for robust control.
Practical and Rigorous Uncertainty Bounds for Gaussian Process Regression
However, these estimates are of a Bayesian nature, whereas for some important applications, like learning-based control with safety guarantees, frequentist uncertainty bounds are required.
Combining Prior Knowledge and Data for Robust Controller Design
We present a framework for systematically combining data of an unknown linear time-invariant system with prior knowledge on the system matrices or on the uncertainty for robust controller design.
