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Thomas Beckers
Thomas Beckers
Verified email at vanderbilt.edu - Homepage
Title
Cited by
Cited by
Year
Stable Gaussian process based tracking control of Euler–Lagrange systems
T Beckers, D Kulić, S Hirche
Automatica 103, 390-397, 2019
1222019
Feedback linearization using Gaussian processes
J Umlauft, T Beckers, M Kimmel, S Hirche
2017 IEEE 56th Annual Conference on Decision and Control (CDC), 5249-5255, 2017
762017
Scenario-based optimal control for Gaussian process state space models
J Umlauft, T Beckers, S Hirche
2018 European Control Conference (ECC), 1386-1392, 2018
382018
Stability of Gaussian process state space models
T Beckers, S Hirche
2016 European Control Conference (ECC), 2275-2281, 2016
372016
Localized active learning of Gaussian process state space models
A Capone, G Noske, J Umlauft, T Beckers, A Lederer, S Hirche
Learning for Dynamics and Control, 490-499, 2020
342020
Equilibrium distributions and stability analysis of Gaussian process state space models
T Beckers, S Hirche
2016 IEEE 55th Conference on Decision and Control (CDC), 6355-6361, 2016
342016
Stable model-based control with Gaussian process regression for robot manipulators
T Beckers, J Umlauft, S Hirche
IFAC-PapersOnLine 50 (1), 3877-3884, 2017
312017
Stable Gaussian process based tracking control of Lagrangian systems
T Beckers, J Umlauft, D Kulic, S Hirche
2017 IEEE 56th Annual Conference on Decision and Control (CDC), 5180-5185, 2017
292017
An introduction to gaussian process models
T Beckers
arXiv preprint arXiv:2102.05497, 2021
282021
Smart forgetting for safe online learning with Gaussian processes
J Umlauft, T Beckers, A Capone, A Lederer, S Hirche
Learning for dynamics and control, 160-169, 2020
262020
Mean square prediction error of misspecified Gaussian process models
T Beckers, J Umlauft, S Hirche
2018 IEEE Conference on Decision and Control (CDC), 1162-1167, 2018
262018
Prediction with approximated Gaussian process dynamical models
T Beckers, S Hirche
IEEE Transactions on Automatic Control 67 (12), 6460-6473, 2021
162021
The impact of data on the stability of learning-based control
A Lederer, A Capone, T Beckers, J Umlauft, S Hirche
Learning for Dynamics and Control, 623-635, 2021
162021
Gaussian process-based visual pursuit control with unknown target motion learning in three dimensions
M Omainska, J Yamauchi, T Beckers, T Hatanaka, S Hirche, M Fujita
SICE Journal of Control, Measurement, and System Integration 14 (1), 116-127, 2021
132021
Online learning-based trajectory tracking for underactuated vehicles with uncertain dynamics
T Beckers, LJ Colombo, S Hirche, GJ Pappas
IEEE Control Systems Letters 6, 2090-2095, 2021
11*2021
A slotted waveguide setup as scaled instrument-landing-system for measuring scattering of an A380 and large objects
R Geise, J Schueuer, L Thiele, K Notté, T Beckers, A Enders
Proceedings of the Fourth European Conference on Antennas and Propagation, 1-5, 2010
112010
Geometric control for load transportation with quadrotor uavs by elastic cables
JR Goodman, T Beckers, LJ Colombo
IEEE Transactions on Control Systems Technology, 2023
102023
Gaussian process port-Hamiltonian systems: Bayesian learning with physics prior
T Beckers, J Seidman, P Perdikaris, GJ Pappas
2022 IEEE 61st Conference on Decision and Control (CDC), 1447-1453, 2022
102022
Closed-loop model selection for kernel-based models using bayesian optimization
T Beckers, S Bansal, CJ Tomlin, S Hirche
2019 IEEE 58th Conference on Decision and Control (CDC), 828-834, 2019
72019
Online learning-based formation control of multi-agent systems with Gaussian processes
T Beckers, S Hirche, L Colombo
2021 60th IEEE Conference on Decision and Control (CDC), 2197-2202, 2021
52021
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