| Deep predictive policy training using reinforcement learning A Ghadirzadeh, A Maki, D Kragic, M Björkman 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2017 | 114 | 2017 |
| A sensorimotor reinforcement learning framework for physical human-robot interaction A Ghadirzadeh, J Bütepage, A Maki, D Kragic, M Björkman 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2016 | 41 | 2016 |
| Meta reinforcement learning for sim-to-real domain adaptation K Arndt, M Hazara, A Ghadirzadeh, V Kyrki 2020 IEEE International Conference on Robotics and Automation (ICRA), 2725-2731, 2020 | 40 | 2020 |
| Deep reinforcement learning to acquire navigation skills for wheel-legged robots in complex environments X Chen, A Ghadirzadeh, J Folkesson, M Björkman, P Jensfelt 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2018 | 39 | 2018 |
| Affordance learning for end-to-end visuomotor robot control A Hämäläinen, K Arndt, A Ghadirzadeh, V Kyrki 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2019 | 31 | 2019 |
| Human-centered collaborative robots with deep reinforcement learning A Ghadirzadeh, X Chen, W Yin, Z Yi, M Björkman, D Kragic IEEE Robotics and Automation Letters 6 (2), 566-571, 2020 | 23 | 2020 |
| Meta-learning for multi-objective reinforcement learning X Chen, A Ghadirzadeh, M Björkman, P Jensfelt 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2019 | 17 | 2019 |
| Adversarial feature training for generalizable robotic visuomotor control X Chen, A Ghadirzadeh, M Björkman, P Jensfelt 2020 IEEE International Conference on Robotics and Automation (ICRA), 1142-1148, 2020 | 15 | 2020 |
| Self-learning and adaptation in a sensorimotor framework A Ghadirzadeh, J Bütepage, D Kragic, M Björkman 2016 IEEE International Conference on Robotics and Automation (ICRA), 551-558, 2016 | 13 | 2016 |
| Imitating by generating: Deep generative models for imitation of interactive tasks J Bütepage, A Ghadirzadeh, Ö Öztimur Karadaǧ, M Björkman, D Kragic Frontiers in Robotics and AI 7, 47, 2020 | 11 | 2020 |
| Data-efficient visuomotor policy training using reinforcement learning and generative models A Ghadirzadeh, P Poklukar, V Kyrki, D Kragic, M Björkman arXiv preprint arXiv:2007.13134, 2020 | 9 | 2020 |
| A sensorimotor approach for self-learning of hand-eye coordination A Ghadirzadeh, A Maki, M Björkman 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2015 | 9 | 2015 |
| Learning visual forward models to compensate for self-induced image motion A Ghadirzadeh, G Kootstra, A Maki, M Björkman Robot and Human Interactive Communication, 2014 RO-MAN: The 23rd IEEE …, 2014 | 8 | 2014 |
| Few-shot model-based adaptation in noisy conditions K Arndt, A Ghadirzadeh, M Hazara, V Kyrki IEEE Robotics and Automation Letters 6 (2), 4193-4200, 2021 | 6 | 2021 |
| Sensorimotor robot policy training using reinforcement learning A Ghadirzadeh KTH Royal Institute of Technology, 2018 | 6 | 2018 |
| Bayesian Meta-Learning for Few-Shot Policy Adaptation Across Robotic Platforms A Ghadirzadeh, X Chen, P Poklukar, C Finn, M Björkman, D Kragic 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2021 | 5 | 2021 |
| Exploring temporal dependencies in multimodal referring expressions with mixed reality E Sibirtseva, A Ghadirzadeh, I Leite, M Björkman, D Kragic International Conference on Human-Computer Interaction, 108-123, 2019 | 4 | 2019 |
| Skew-explore: Learn faster in continuous spaces with sparse rewards X Chen, Y Gao, A Ghadirzadeh, M Bjorkman, G Castellano, P Jensfelt | 2 | 2019 |
| Training and evaluation of deep policies using reinforcement learning and generative models A Ghadirzadeh, P Poklukar, K Arndt, C Finn, V Kyrki, D Kragic, ... arXiv preprint arXiv:2204.08573, 2022 | 1 | 2022 |
| Latent-Variable Advantage-Weighted Policy Optimization for Offline RL X Chen, A Ghadirzadeh, T Yu, Y Gao, J Wang, W Li, B Liang, C Finn, ... arXiv preprint arXiv:2203.08949, 2022 | 1 | 2022 |
Mårten BjörkmanKTH Royal Institute of TechnologyVerified email at csc.kth.se
