Sotabase

Career

· Postdoctoral Researcher, ETH Zurich2025–2025
· Assistant Professor, National University of Singapore2025–
· Professor, NUS
· Bachelor's degree, Technical University of Munich
· Master's Degree, Technical University of Munich
· PhD Student, Technical University of Munich

Publications (51)

Uniform Error Bounds for Gaussian Process Regression with Application to Safe Control
Neural Information Processing Systems · 2019
171
cited
Gaussian Process-Based Real-Time Learning for Safety Critical Applications
International Conference on Machine Learning · 2021
42
cited
Learning stable Gaussian process state space models
American Control Conference · 2017
42
cited
Cooperative Control of Uncertain Multiagent Systems via Distributed Gaussian Processes
IEEE Transactions on Automatic Control · 2023
41
cited
Localized active learning of Gaussian process state space models
Conference on Learning for Dynamics & Control · 2020
29
cited
Diffeomorphically Learning Stable Koopman Operators
IEEE Control Systems Letters · 2021
27
cited
Koopman Kernel Regression
Neural Information Processing Systems · 2023
27
cited
Gaussian Process Uniform Error Bounds with Unknown Hyperparameters for Safety-Critical Applications
International Conference on Machine Learning · 2021
26
cited
Posterior Variance Analysis of Gaussian Processes with Application to Average Learning Curves
arXiv.org · 2019
26
cited
Uniform Error and Posterior Variance Bounds for Gaussian Process Regression with Application to Safe Control
arXiv.org · 2021
23
cited
Smart Forgetting for Safe Online Learning with Gaussian Processes
Conference on Learning for Dynamics & Control · 2020
21
cited
How Training Data Impacts Performance in Learning-Based Control
IEEE Control Systems Letters · 2020
20
cited
KoopmanizingFlows: Diffeomorphically Learning Stable Koopman Operators
arXiv.org · 2021
18
cited
Distributed Learning Consensus Control for Unknown Nonlinear Multi-Agent Systems based on Gaussian Processes
IEEE Conference on Decision and Control · 2021
16
cited
Can Learning Deteriorate Control? Analyzing Computational Delays in Gaussian Process-Based Event-Triggered Online Learning
Conference on Learning for Dynamics & Control · 2023
15
cited
Local Asymptotic Stability Analysis and Region of Attraction Estimation with Gaussian Processes*
IEEE Conference on Decision and Control · 2019
14
cited
Parameter Optimization for Learning-based Control of Control-Affine Systems
Conference on Learning for Dynamics & Control · 2020
13
cited
Real-Time Regression with Dividing Local Gaussian Processes
arXiv.org · 2020
12
cited
Data Selection for Multi-Task Learning Under Dynamic Constraints
IEEE Control Systems Letters · 2020
11
cited
The Impact of Data on the Stability of Learning-Based Control
Conference on Learning for Dynamics & Control · 2020
11
cited
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Armin Lederer | Researcher Profile | Sotabase | Sotabase