| Uniform error bounds for Gaussian process regression with application to safe control A Lederer, J Umlauft, S Hirche Advances in Neural Information Processing Systems 32, 659-669, 2019 | 149 | 2019 |
| Gaussian process-based real-time learning for safety critical applications A Lederer, AJO Conejo, KA Maier, W Xiao, J Umlauft, S Hirche International Conference on Machine Learning, 6055-6064, 2021 | 45* | 2021 |
| Learning stable Gaussian process state space models J Umlauft, A Lederer, S Hirche 2017 American Control Conference (ACC), 1499-1504, 2017 | 42 | 2017 |
| 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 | 31 | 2020 |
| 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 | 25 | 2020 |
| Diffeomorphically learning stable Koopman operators P Bevanda, M Beier, S Kerz, A Lederer, S Sosnowski, S Hirche IEEE Control Systems Letters 6, 3427-3432, 2022 | 22* | 2022 |
| How training data impacts performance in learning-based control A Lederer, A Capone, J Umlauft, S Hirche IEEE Control Systems Letters 5 (3), 905-910, 2020 | 22 | 2020 |
| Gaussian process uniform error bounds with unknown hyperparameters for safety-critical applications A Capone, A Lederer, S Hirche International Conference on Machine Learning, 2609-2624, 2022 | 18 | 2022 |
| Posterior variance analysis of Gaussian processes with application to average learning curves A Lederer, J Umlauft, S Hirche arXiv preprint arXiv:1906.01404, 2019 | 18 | 2019 |
| 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 | 16 | 2021 |
| Uniform error and posterior variance bounds for Gaussian process regression with application to safe control A Lederer, J Umlauft, S Hirche arXiv preprint arXiv:2101.05328, 2021 | 15 | 2021 |
| Parameter Optimization for Learning-based Control of Control-Affine Systems A Lederer, A Capone, S Hirche Learning for Dynamics and Control, 465-475, 2020 | 15 | 2020 |
| Distributed learning consensus control for unknown nonlinear multi-agent systems based on gaussian processes Z Yang, S Sosnowski, Q Liu, J Jiao, A Lederer, S Hirche 2021 60th IEEE Conference on Decision and Control (CDC), 4406-4411, 2021 | 13 | 2021 |
| Can learning deteriorate control? analyzing computational delays in gaussian process-based event-triggered online learning X Dai, A Lederer, Z Yang, S Hirche Learning for Dynamics and Control Conference, 445-457, 2023 | 12* | 2023 |
| Cooperative control of uncertain multi-agent systems via distributed gaussian processes A Lederer, Z Yang, J Jiao, S Hirche IEEE Transactions on Automatic Control, 2022 | 12 | 2022 |
| Data selection for multi-task learning under dynamic constraints A Capone, A Lederer, J Umlauft, S Hirche IEEE Control Systems Letters 5 (3), 959-964, 2020 | 12 | 2020 |
| Local asymptotic stability analysis and region of attraction estimation with gaussian processes A Lederer, S Hirche 2019 IEEE 58th Conference on Decision and Control (CDC), 1766-1771, 2019 | 12 | 2019 |
| Koopman kernel regression P Bevanda, M Beier, A Lederer, S Sosnowski, E Hüllermeier, S Hirche Advances in Neural Information Processing Systems 36, 2024 | 7 | 2024 |
| Learning stable nonparametric dynamical systems with Gaussian process regression W Xiao, A Lederer, S Hirche IFAC-PapersOnLine 53 (2), 1194-1199, 2020 | 7 | 2020 |
| Deep Learning based Uncertainty Decomposition for Real-time Control N Das, J Umlauft, A Lederer, A Capone, T Beckers, S Hirche IFAC-PapersOnLine 56 (2), 847-853, 2023 | 5* | 2023 |
Sandra HircheTechnical University of MunichVerified email at tum.de
