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Lukas Theiner
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[i6]Lukas Theiner, Maik Pfefferkorn, Yongpeng Zhao, Sebastian Hirt, Rolf Findeisen:
Efficient Controller Learning from Human Preferences and Numerical Data Via Multi-Modal Surrogate Models. CoRR abs/2603.24138 (2026)
[i5]Alexander Rose, Lukas Theiner, Rolf Findeisen:
Real-time Gaussian Process based Approximate Model Predictive Trajectory Tracking Control for Autonomous Vehicles. CoRR abs/2605.13220 (2026)- 2025
[c3]Sebastian Hirt, Lukas Theiner
, Maik Pfefferkorn, Rolf Findeisen:
A Hierarchical Surrogate Model for Efficient Multi-Task Parameter Learning in Closed-Loop Control. CDC 2025: 4578-4585
[c2]Lukas Theiner
, Sebastian Hirt, Alexander Steinke, Rolf Findeisen:
Exploiting Prior Knowledge in Preferential Learning of Individualized Autonomous Vehicle Driving Styles. ECC 2025: 2217-2222
[i4]Hendrik Alsmeier, Lukas Theiner, Anton Savchenko, Ali Mesbah, Rolf Findeisen:
Imitation Learning of MPC with Neural Networks: Error Guarantees and Sparsification. CoRR abs/2501.03671 (2025)
[i3]Lukas Theiner, Sebastian Hirt, Alexander Steinke, Rolf Findeisen:
Exploiting Prior Knowledge in Preferential Learning of Individualized Autonomous Vehicle Driving Styles. CoRR abs/2503.15407 (2025)
[i2]Sebastian Hirt, Lukas Theiner, Maik Pfefferkorn, Rolf Findeisen:
A Hierarchical Surrogate Model for Efficient Multi-Task Parameter Learning in Closed-Loop Control. CoRR abs/2508.12738 (2025)- 2024
[c1]Hendrik Alsmeier, Lukas Theiner
, Anton Savchenko, Ali Mesbah, Rolf Findeisen:
Imitation Learning of MPC with Neural Networks: Error Guarantees and Sparsification. CDC 2024: 4777-4782
[i1]Sebastian Hirt, Lukas Theiner, Rolf Findeisen:
Time-Series-Informed Closed-loop Learning for Sequential Decision Making and Control. CoRR abs/2412.02423 (2024)
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