Stable Gaussian process based tracking control of Euler–Lagrange systems T Beckers, D Kulić, S Hirche Automatica 103, 390-397, 2019 | 141 | 2019 |
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 | 79 | 2017 |
Stability of Gaussian process state space models T Beckers, S Hirche 2016 European Control Conference (ECC), 2275-2281, 2016 | 43 | 2016 |
An introduction to gaussian process models T Beckers arXiv preprint arXiv:2102.05497, 2021 | 40 | 2021 |
Scenario-based optimal control for Gaussian process state space models J Umlauft, T Beckers, S Hirche 2018 European Control Conference (ECC), 1386-1392, 2018 | 40 | 2018 |
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 | 36 | 2020 |
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 | 36 | 2016 |
Stable model-based control with Gaussian process regression for robot manipulators T Beckers, J Umlauft, S Hirche IFAC-PapersOnLine 50 (1), 3877-3884, 2017 | 32 | 2017 |
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 | 30 | 2017 |
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 | 29 | 2020 |
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 | 26 | 2018 |
Prediction with approximated Gaussian process dynamical models T Beckers, S Hirche IEEE Transactions on Automatic Control 67 (12), 6460-6473, 2021 | 23 | 2021 |
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 | 19 | 2021 |
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 | 17 | 2022 |
Geometric control for load transportation with quadrotor uavs by elastic cables JR Goodman, T Beckers, LJ Colombo IEEE Transactions on Control Systems Technology, 2023 | 16 | 2023 |
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 | 15 | 2021 |
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 | 14* | 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 | 12 | 2010 |
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 | 8 | 2019 |
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 | 7 | 2021 |