| Data-efficient generalization of robot skills with contextual policy search A Kupcsik, M Deisenroth, J Peters, G Neumann Proceedings of the AAAI conference on artificial intelligence 27 (1), 1401-1407, 2013 | 141 | 2013 |
| Model-based contextual policy search for data-efficient generalization of robot skills A Kupcsik, MP Deisenroth, J Peters, AP Loh, P Vadakkepat, G Neumann Artificial Intelligence 247, 415-439, 2017 | 96 | 2017 |
| Learning dynamic robot-to-human object handover from human feedback A Kupcsik, D Hsu, WS Lee Robotics Research: Volume 1, 161-176, 2018 | 76 | 2018 |
| Dexterous underwater manipulation from onshore locations: Streamlining efficiencies for remotely operated underwater vehicles A Birk, T Doernbach, C Mueller, T Łuczynski, AG Chavez, D Koehntopp, ... IEEE Robotics & Automation Magazine 25 (4), 24-33, 2018 | 54 | 2018 |
| Learning modular policies for robotics G Neumann, C Daniel, A Paraschos, A Kupcsik, J Peters Frontiers in computational neuroscience 8, 62, 2014 | 28 | 2014 |
| Data-efficient contextual policy search for robot movement skills A Kupcsik, MP Deisenroth, J Peters, G Neumann Proceedings of the National Conference on Artificial Intelligence (AAAI), 2013 | 26 | 2013 |
| Learning and sequencing of object-centric manipulation skills for industrial tasks L Rozo, M Guo, AG Kupcsik, M Todescato, P Schillinger, M Giftthaler, ... 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2020 | 20 | 2020 |
| The kernel Kalman rule—Efficient nonparametric inference with recursive least squares G Gebhardt, A Kupcsik, G Neumann Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 18 | 2017 |
| Learning forceful manipulation skills from multi-modal human demonstrations AT Le, M Guo, N van Duijkeren, L Rozo, R Krug, AG Kupcsik, M Bürger 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2021 | 16 | 2021 |
| The kernel kalman rule: Efficient nonparametric inference by recursive least-squares and subspace projections GHW Gebhardt, A Kupcsik, G Neumann Machine Learning 108 (12), 2113-2157, 2019 | 11 | 2019 |
| Information-theoretic motor skill learning G Neumann, C Daniel, A Kupcsik, M Deisenroth, J Peters Workshops at the Twenty-Seventh AAAI Conference on Artificial Intelligence, 2013 | 10 | 2013 |
| Supervised training of dense object nets using optimal descriptors for industrial robotic applications AG Kupcsik, M Spies, A Klein, M Todescato, N Waniek, P Schillinger, ... Proceedings of the AAAI Conference on Artificial Intelligence 35 (7), 6093-6100, 2021 | 9 | 2021 |
| Factored contextual policy search with bayesian optimization R Pinsler, P Karkus, A Kupcsik, D Hsu, WS Lee 2019 International Conference on Robotics and Automation (ICRA), 7242-7248, 2019 | 5 | 2019 |
| Factored contextual policy search with Bayesian optimization P Karkus, A Kupcsik, D Hsu, WS Lee arXiv preprint arXiv:1612.01746, 2016 | 5 | 2016 |
| Learning subspace conditional embedding operators GHW Gebhardt, A Kupcsik, G Neumann Workshop on Large-Scale Kernel Learning at ICML 2015, 2015 | 5 | 2015 |
| Synthetical benchmarking of service robots: a first effort on domestic mobile platforms M Cheng, X Chen, K Tang, F Wu, A Kupcsik, L Iocchi, Y Chen, D Hsu RoboCup 2015: Robot World Cup XIX 19, 377-388, 2015 | 4 | 2015 |
| Learning Dense Visual Descriptors using Image Augmentations for Robot Manipulation Tasks C Graf, DB Adrian, J Weil, M Gabriel, P Schillinger, M Spies, H Neumann, ... Conference on Robot Learning, 871-880, 2023 | 3 | 2023 |
| Efficient and robust training of dense object nets for multi-object robot manipulation DB Adrian, AG Kupcsik, M Spies, H Neumann 2022 International Conference on Robotics and Automation (ICRA), 1562-1568, 2022 | 3 | 2022 |
| Adversarial Imitation Learning with Preferences A Taranovic, AG Kupcsik, N Freymuth, G Neumann The Eleventh International Conference on Learning Representations, 2022 | 2 | 2022 |
| Apparatus and method for training a machine learning model to recognize an object topology of an object from an image of the object AG Kupcsik, M Todescato, M Spies, N Waniek, PC Schillinger, M Buerger US Patent App. 17/454,208, 2022 | 1 | 2022 |
Gerhard NeumannProfessor, Karlsruhe Institute of Technology (KIT)Verified email at robot-learning.de
