| Depth from videos in the wild: Unsupervised monocular depth learning from unknown cameras A Gordon, H Li, R Jonschkowski, A Angelova Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 430 | 2019 |
| Scaling up multi-task robotic reinforcement learning D Kalashnikov, J Varley, Y Chebotar, B Swanson, R Jonschkowski, ... 5th Annual Conference on Robot Learning, 2021 | 264* | 2021 |
| Lessons from the Amazon Picking Challenge: Four Aspects of Building Robotic Systems C Eppner, S Höfer, R Jonschkowski, R Martín-Martín, A Sieverling, V Wall, ... Proceedings of Robotics: Science and Systems, 2016 | 255 | 2016 |
| Learning State Representations with Robotic Priors R Jonschkowski, O Brock Autonomous Robots 39 (3), 407-428, 2015 | 227 | 2015 |
| What Matters in Unsupervised Optical Flow R Jonschkowski, A Stone, JT Barron, A Gordon, K Konolige, A Angelova European Conference on Computer Vision, 2020 | 205 | 2020 |
| Conditional object-centric learning from video T Kipf, GF Elsayed, A Mahendran, A Stone, S Sabour, G Heigold, ... arXiv preprint arXiv:2111.12594, 2021 | 179 | 2021 |
| Differentiable Particle Filters: End-to-End Learning with Algorithmic Priors R Jonschkowski, D Rastogi, O Brock Proceedings of Robotics: Science and Systems, 2018 | 143 | 2018 |
| Keypose: Multi-view 3d labeling and keypoint estimation for transparent objects X Liu, R Jonschkowski, A Angelova, K Konolige Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 111 | 2020 |
| Smurf: Self-teaching multi-frame unsupervised raft with full-image warping A Stone, D Maurer, A Ayvaci, A Angelova, R Jonschkowski Proceedings of the IEEE/CVF conference on Computer Vision and Pattern …, 2021 | 88 | 2021 |
| The Distracting Control Suite--A Challenging Benchmark for Reinforcement Learning from Pixels A Stone, O Ramirez, K Konolige, R Jonschkowski arXiv preprint arXiv:2101.02722, 2021 | 83 | 2021 |
| Probabilistic Multi-Class Segmentation for the Amazon Picking Challenge R Jonschkowski, C Eppner, S Höfer, R Martín-Martín, O Brock IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016 | 81 | 2016 |
| PVEs: Position-Velocity Encoders for Unsupervised Learning of Structured State Representations R Jonschkowski, R Hafner, J Scholz, M Riedmiller New Frontiers for Deep Learning in Robotics Workshop at RSS, 2017 | 72 | 2017 |
| State Representation Learning in Robotics: Using Prior Knowledge about Physical Interaction R Jonschkowski, O Brock Proceedings of Robotics: Science and Systems, 2014 | 62 | 2014 |
| Patterns for Learning with Side Information R Jonschkowski, S Höfer, O Brock arXiv preprint arXiv:1511.06429, 2015 | 48 | 2015 |
| End-To-End Learnable Histogram Filters R Jonschkowski, O Brock Workshop on Deep Learning for Action and Interaction at NeurIPS, 2016 | 40 | 2016 |
| Four aspects of building robotic systems: lessons from the amazon picking challenge 2015 C Eppner, S Höfer, R Jonschkowski, R Martín-Martín, A Sieverling, V Wall, ... Autonomous Robots 42 (7), 1459-1475, 2018 | 31 | 2018 |
| Towards Differentiable Resampling M Zhu, K Murphy, R Jonschkowski RSS Workshop on Structured Approaches to Robot Learning for Improved …, 2020 | 26 | 2020 |
| Learning Object-Centric Video Models by Contrasting Sets S Löwe, K Greff, R Jonschkowski, A Dosovitskiy, T Kipf NeurIPS Workshop on Object Representations for Learning and Reasoning, 2020 | 16 | 2020 |
| Differentiable Mapping Networks: Learning Structured Map Representations for Sparse Visual Localization P Karkus, A Angelova, V Vanhoucke, R Jonschkowski International Conference on Robotics and Automation, 2020 | 13 | 2020 |
| Learning Task-Specific State Representations by Maximizing Slowness and Predictability R Jonschkowski, O Brock Proceedings of the 6th International Workshop on Evolutionary and …, 2013 | 13 | 2013 |
Oliver BrockProfessor of Computer Science, Technische Universität Berlin在 tu-berlin.de 的电子邮件经过验证
