Equilibrium distributions and stability analysis of Gaussian Process State Space Models. - Thomas Beckers 001; Sandra Hirche (CDC, 2016)

Stability of Gaussian process state space models. - Thomas Beckers 001; Sandra Hirche (ECC, 2016)

Stable Gaussian process based tracking control of Lagrangian systems. - Thomas Beckers 001; Jonas Umlauft; Dana Kulic; Sandra Hirche (CDC, 2017)

Feedback linearization using Gaussian processes. - Jonas Umlauft; Thomas Beckers 001; Melanie Kimmel; Sandra Hirche (CDC, 2017)

Mean Square Prediction Error of Misspecified Gaussian Process Models. - Thomas Beckers 001; Jonas Umlauft; Sandra Hirche (CDC, 2018)

Gaussian Process based Passivation of a Class of Nonlinear Systems with Unknown Dynamics. - Thomas Beckers 001; Sandra Hirche (ECC, 2018)

Scenario-based Optimal Control for Gaussian Process State Space Models. - Jonas Umlauft; Thomas Beckers 001; Sandra Hirche (ECC, 2018)

Stable Model-based Control with Gaussian Process Regression for Robot Manipulators. - Thomas Beckers 001; Jonas Umlauft; Sandra Hirche (CoRR, 2018)

Closed-loop Model Selection for Kernel-based Models using Bayesian Optimization. - Thomas Beckers 001; Somil Bansal; Claire J. Tomlin; Sandra Hirche (CDC, 2019)

Stable Gaussian process based tracking control of Euler-Lagrange systems. - Thomas Beckers 001; Dana Kulic; Sandra Hirche (Autom., 2019)

Keep soft robots soft - a data-driven based trade-off between feed-forward and feedback control. - Thomas Beckers 001; Sandra Hirche (CoRR, 2019)

Localized active learning of Gaussian process state space models. - Alexandre Capone; Gerrit Noske; Jonas Umlauft; Thomas Beckers 001; Armin Lederer; Sandra Hirche (L4DC, 2020)

Smart Forgetting for Safe Online Learning with Gaussian Processes. - Jonas Umlauft; Thomas Beckers 001; Alexandre Capone; Armin Lederer; Sandra Hirche (L4DC, 2020)

Visual Pursuit Control with Target Motion Learning via Gaussian Process. - Junya Yamauchi; Thomas Beckers 001; Marco Omainska; Takeshi Hatanaka; Sandra Hirche; Masayuki Fujita (SICE, 2020)

Localized active learning of Gaussian process state space models. - Alexandre Capone; Jonas Umlauft; Thomas Beckers 001; Armin Lederer; Sandra Hirche (CoRR, 2020)

Prediction with Gaussian Process Dynamical Models. - Thomas Beckers 001; Sandra Hirche (CoRR, 2020)

Safe learning-based trajectory tracking for underactuated vehicles with partially unknown dynamics. - Thomas Beckers 001; Leonardo Colombo; Sandra Hirche (CoRR, 2020)

Real-time Uncertainty Decomposition for Online Learning Control. - Jonas Umlauft; Armin Lederer; Thomas Beckers 001; Sandra Hirche (CoRR, 2020)

The Value of Data in Learning-Based Control for Training Subset Selection. - Armin Lederer; Alexandre Capone; Thomas Beckers 001; Jonas Umlauft; Sandra Hirche (CoRR, 2020)

Online Learning-based Formation Control of Multi-Agent Systems with Gaussian Processes. - Thomas Beckers 001; Sandra Hirche; Leonardo Colombo (CDC, 2021)

Cooperative Visual Pursuit Control with Learning of Position Dependent Target Motion via Gaussian Process. - Junya Yamauchi; Marco Omainska; Thomas Beckers 001; Takeshi Hatanaka; Sandra Hirche; Masayuki Fujita (CDC, 2021)

The Impact of Data on the Stability of Learning-Based Control. - Armin Lederer; Alexandre Capone; Thomas Beckers 001; Jonas Umlauft; Sandra Hirche (L4DC, 2021)

An Introduction to Gaussian Process Models. - Thomas Beckers 001 (CoRR, 2021)

Safe Online Learning-based Formation Control of Multi-Agent Systems with Gaussian Processes. - Thomas Beckers 001; Sandra Hirche; Leonardo Colombo (CoRR, 2021)

Geometric Control for Load Transportation with Quadrotor UAVs by Elastic Cables. - Jacob R. Goodman; Juan S. Cely; Thomas Beckers 001; Leonardo J. Colombo (CoRR, 2021)

Learning Rigidity-based Flocking Control with Gaussian Processes. - Manuela Gamonal Fernández; Thomas Beckers 001; George J. Pappas; Leonardo J. Colombo (CoRR, 2021)

Learning-based Balancing of Model-based and Feedback Control for Second-order Mechanical Systems. - Thomas Beckers 001; Leonardo J. Colombo; Manfred Morari; George J. Pappas (CDC, 2022)

Learning Rigidity-based Flocking Control using Gaussian Processes with Probabilistic Stability Guarantees. - Thomas Beckers 001; George J. Pappas; Leonardo J. Colombo (CDC, 2022)

Gaussian Process Port-Hamiltonian Systems: Bayesian Learning with Physics Prior. - Thomas Beckers 001; Jacob H. Seidman; Paris Perdikaris; George J. Pappas (CDC, 2022)

Online Learning-Based Trajectory Tracking for Underactuated Vehicles With Uncertain Dynamics. - Thomas Beckers 001; Leonardo J. Colombo; Sandra Hirche; George J. Pappas (IEEE Control. Syst. Lett., 2022)

Prediction With Approximated Gaussian Process Dynamical Models. - Thomas Beckers 001; Sandra Hirche (IEEE Trans. Autom. Control., 2022)

Data-Driven Bayesian Control of Port-Hamiltonian Systems. - Thomas Beckers 001 (CDC, 2023)

Physics-enhanced Gaussian Process Variational Autoencoder. - Thomas Beckers 001; Qirui Wu; George J. Pappas (L4DC, 2023)

Learning Switching Port-Hamiltonian Systems with Uncertainty Quantification. - Thomas Beckers 001; Tom Z. Jiahao; George J. Pappas (CoRR, 2023)

Geometric Control for Load Transportation With Quadrotor UAVs by Elastic Cables. - Jacob R. Goodman; Thomas Beckers 001; Leonardo J. Colombo (IEEE Trans. Control. Syst. Technol., 2023)

Interpretable Finite State Machine Controller: A Case Study on Lane Merge Yield Mode. - Xia Wang; Yuwei Yang; Yifan Shangguan; Weiyu Yan; Ziyan An; Matthew R. Bunting; Matthew Nice; Thomas Beckers 001; Meiyi Ma; Dan Work; Jonathan Sprinkle (ITSC, 2024)

Physics-constrained learning for PDE systems with uncertainty quantified port-Hamiltonian models. - Kaiyuan Tan; Peilun Li; Thomas Beckers 001 (L4DC, 2024)

Safe Physics-informed Machine Learning for Dynamics and Control. - Ján Drgona; Truong X. Nghiem; Thomas Beckers 001; Mahyar Fazlyab; Enrique Mallada; Colin N. Jones; Draguna L. Vrabie; Steven L. Brunton; Rolf Findeisen (ACC, 2025)

NAPI-MPC: Neural Accelerated Physics-Informed MPC for Nonlinear PDE Systems. - Peilun Li; Kaiyuan Tan; Thomas Beckers 001 (L4DC, 2025)

Plug-and-Play Physics-informed Learning using Uncertainty Quantified Port-Hamiltonian Models. - Kaiyuan Tan; Peilun Li; Jun Wang; Thomas Beckers 001 (CoRR, 2025)

Physics-informed Learning for Passivity-based Tracking Control. - Thomas Beckers 001; Leonardo Colombo (CoRR, 2025)