| Reverse curriculum generation for reinforcement learning C Florensa, D Held, M Wulfmeier, M Zhang, P Abbeel Conference on robot learning, 482-495, 2017 | 303 | 2017 |
| Maximum entropy deep inverse reinforcement learning M Wulfmeier, P Ondruska, I Posner arXiv preprint arXiv:1507.04888, 2015 | 293 | 2015 |
| Large-scale cost function learning for path planning using deep inverse reinforcement learning M Wulfmeier, D Rao, DZ Wang, P Ondruska, I Posner The International Journal of Robotics Research 36 (10), 1073-1087, 2017 | 110 | 2017 |
| Watch this: Scalable cost-function learning for path planning in urban environments M Wulfmeier, DZ Wang, I Posner 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2016 | 100 | 2016 |
| Incremental Adversarial Domain Adaptation for Continually Changing Environments M Wulfmeier, A Bewley, I Posner arXiv preprint arXiv:1712.07436, 2017 | 82 | 2017 |
| Addressing appearance change in outdoor robotics with adversarial domain adaptation M Wulfmeier, A Bewley, I Posner 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2017 | 67 | 2017 |
| Deep inverse reinforcement learning M Wulfmeier, P Ondruska, I Posner CoRR, abs/1507.04888, 2015 | 62 | 2015 |
| Mutual alignment transfer learning M Wulfmeier, I Posner, P Abbeel Conference on Robot Learning, 281-290, 2017 | 52 | 2017 |
| Taco: Learning task decomposition via temporal alignment for control K Shiarlis, M Wulfmeier, S Salter, S Whiteson, I Posner International Conference on Machine Learning, 4654-4663, 2018 | 51 | 2018 |
| Design and implementation of a particle image velocimetry method for analysis of running gear–soil interaction C Senatore, M Wulfmeier, I Vlahinić, J Andrade, K Iagnemma Journal of Terramechanics 50 (5-6), 311-326, 2013 | 50 | 2013 |
| Compositional Transfer in Hierarchical Reinforcement Learning M Wulfmeier, A Abdolmaleki, R Hafner, JT Springenberg, M Neunert, ... | 35* | 2019 |
| Continuous-discrete reinforcement learning for hybrid control in robotics M Neunert, A Abdolmaleki, M Wulfmeier, T Lampe, T Springenberg, ... Conference on Robot Learning, 735-751, 2020 | 32 | 2020 |
| Investigation of stress and failure in granular soils for lightweight robotic vehicle applications C Senatore, M Wulfmeier, J MacLennan, P Jayakumar, K Iagnemma ARMY TANK AUTOMOTIVE RESEARCH DEVELOPMENT AND ENGINEERING CENTER WARREN MI, 2012 | 25 | 2012 |
| Voronoi-based heuristic for nonholonomic search-based path planning Q Wang, M Wulfmeier, B Wagner Intelligent Autonomous Systems 13, 445-458, 2016 | 17* | 2016 |
| Disentangled cumulants help successor representations transfer to new tasks C Grimm, I Higgins, A Barreto, D Teplyashin, M Wulfmeier, T Hertweck, ... arXiv preprint arXiv:1911.10866, 2019 | 16 | 2019 |
| Incorporating human domain knowledge into large scale cost function learning M Wulfmeier, D Rao, I Posner arXiv preprint arXiv:1612.04318, 2016 | 14 | 2016 |
| Data-efficient hindsight off-policy option learning M Wulfmeier, D Rao, R Hafner, T Lampe, A Abdolmaleki, T Hertweck, ... International Conference on Machine Learning, 11340-11350, 2021 | 12 | 2021 |
| Attention-privileged reinforcement learning S Salter, D Rao, M Wulfmeier, R Hadsell, I Posner arXiv preprint arXiv:1911.08363, 2019 | 11* | 2019 |
| Towards general and autonomous learning of core skills: A case study in locomotion R Hafner, T Hertweck, P Klöppner, M Bloesch, M Neunert, M Wulfmeier, ... arXiv preprint arXiv:2008.12228, 2020 | 10 | 2020 |
| Neural Stethoscopes: Unifying analytic, auxiliary and adversarial network probing FB Fuchs, O Groth, AR Kosiorek, A Bewley, M Wulfmeier, A Vedaldi, ... arXiv, 2018 | 9* | 2018 |
Ingmar PosnerOxford UniversityVerified email at robots.ox.ac.uk
