Armin Lederer

CoRR, 2023

Learning-Based Optimal Control with Performance Guarantees for Unknown Systems with Latent States.

[BibT_eX]

[DOI]

CoRR, 2023

Koopman Kernel Regression.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Can Learning Deteriorate Control? Analyzing Computational Delays in Gaussian Process-Based Event-Triggered Online Learning.

[BibT_eX]

[DOI]

Proceedings of the Learning for Dynamics and Control Conference, 2023

Risk-Sensitive Inhibitory Control for Safe Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

2022

Diffeomorphically Learning Stable Koopman Operators.

[BibT_eX]

[DOI]

IEEE Control. Syst. Lett., 2022

Safe Learning-Based Control of Elastic Joint Robots via Control Barrier Functions.

[BibT_eX]

[DOI]

CoRR, 2022

Uncertainty-Aware Visual Perception for Safe Motion Planning.

[BibT_eX]

[DOI]

CoRR, 2022

Gaussian Process Uniform Error Bounds with Unknown Hyperparameters for Safety-Critical Applications.

[BibT_eX]

[DOI]

Alexandre Capone

Proceedings of the International Conference on Machine Learning, 2022

Adaptive Low-Pass Filtering using Sliding Window Gaussian Processes.

[BibT_eX]

[DOI]

Proceedings of the European Control Conference, 2022

Safe Reinforcement Learning via Confidence-Based Filters.

[BibT_eX]

[DOI]

Proceedings of the 61st IEEE Conference on Decision and Control, 2022

Networked Online Learning for Control of Safety-Critical Resource-Constrained Systems based on Gaussian Processes.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Control Technology and Applications, 2022

2021

How Training Data Impacts Performance in Learning-Based Control.

[BibT_eX]

[DOI]

IEEE Control. Syst. Lett., 2021

Data Selection for Multi-Task Learning Under Dynamic Constraints.

[BibT_eX]

[DOI]

IEEE Control. Syst. Lett., 2021

KoopmanizingFlows: Diffeomorphically Learning Stable Koopman Operators.

[BibT_eX]

[DOI]

CoRR, 2021

Personalized Rehabilitation Robotics based on Online Learning Control.

[BibT_eX]

[DOI]

Samuel Tesfazgi

Johannes F. Kunz

CoRR, 2021

Uniform Error and Posterior Variance Bounds for Gaussian Process Regression with Application to Safe Control.

[BibT_eX]

[DOI]

CoRR, 2021

The Impact of Data on the Stability of Learning-Based Control.

[BibT_eX]

[DOI]

Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

Gaussian Process-Based Real-Time Learning for Safety Critical Applications.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Distributed Learning Consensus Control for Unknown Nonlinear Multi-Agent Systems based on Gaussian Processes.

[BibT_eX]

[DOI]

Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

Inverse Reinforcement Learning: A Control Lyapunov Approach.

[BibT_eX]

[DOI]

Samuel Tesfazgi

Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

Distributed Bayesian Online Learning for Cooperative Manipulation.

[BibT_eX]

[DOI]

Pablo Budde gen. Dohmann

Marcel Dißemond

Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

2020

The Value of Data in Learning-Based Control for Training Subset Selection.

[BibT_eX]

[DOI]

CoRR, 2020

Real-time Uncertainty Decomposition for Online Learning Control.

[BibT_eX]

[DOI]

CoRR, 2020

Real-Time Regression with Dividing Local Gaussian Processes.

[BibT_eX]

[DOI]

Korbinian Maier

Wenxin Xiao

CoRR, 2020

GP3: A Sampling-based Analysis Framework for Gaussian Processes.

[BibT_eX]

[DOI]

Markus Kessler

CoRR, 2020

Learning Stable Nonparametric Dynamical Systems with Gaussian Process Regression.

[BibT_eX]

[DOI]

Wenxin Xiao

CoRR, 2020

Localized active learning of Gaussian process state space models.

[BibT_eX]

[DOI]

CoRR, 2020

Smart Forgetting for Safe Online Learning with Gaussian Processes.

[BibT_eX]

[DOI]

Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020

Parameter Optimization for Learning-based Control of Control-Affine Systems.

[BibT_eX]

[DOI]

Alexandre Capone

Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020

Localized active learning of Gaussian process state space models.

[BibT_eX]

[DOI]

Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020

Confidence Regions for Simulations with Learned Probabilistic Models.

[BibT_eX]

[DOI]

Qing Hao

Proceedings of the 2020 American Control Conference, 2020

2019

Posterior Variance Analysis of Gaussian Processes with Application to Average Learning Curves.

[BibT_eX]

[DOI]

CoRR, 2019

Uniform Error Bounds for Gaussian Process Regression with Application to Safe Control.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Local Asymptotic Stability Analysis and Region of Attraction Estimation with Gaussian Processes.

[BibT_eX]

[DOI]

Proceedings of the 58th IEEE Conference on Decision and Control, 2019

2017

Learning stable Gaussian process state space models.

[BibT_eX]

[DOI]