| 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 | 145* | 2017 |
| 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 | 90 | 2020 |
| 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 | 57 | 2020 |
| 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 | 54 | 2016 |
| 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 | 52 | 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 | 43 | 2019 |
| 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 | 33 | 2019 |
| Lapo: Latent-variable advantage-weighted policy optimization for offline reinforcement learning X Chen, A Ghadirzadeh, T Yu, J Wang, AY Gao, W Li, L Bin, C Finn, ... Advances in Neural Information Processing Systems 35, 36902-36913, 2022 | 25* | 2022 |
| 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 | 21 | 2021 |
| 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 | 20 | 2020 |
| 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 | 19 | 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 | 13 | 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 |
| 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 | 7 | 2021 |
| Meta-learning for multi-objective reinforcement learning. In 2019 IEEE X Chen, A Ghadirzadeh, M Björkman, P Jensfelt RSJ International Conference on Intelligent Robots and Systems (IROS), 977-983, 2019 | 7* | 2019 |
| Fine-tuning Offline Policies with Optimistic Action Selection MS Mark, A Ghadirzadeh, X Chen, C Finn Deep Reinforcement Learning Workshop NeurIPS 2022, 2022 | 6 | 2022 |
| Exploring temporal dependencies in multimodal referring expressions with mixed reality E Sibirtseva, A Ghadirzadeh, I Leite, M Björkman, D Kragic Virtual, Augmented and Mixed Reality. Applications and Case Studies: 11th …, 2019 | 6 | 2019 |
| Sensorimotor robot policy training using reinforcement learning A Ghadirzadeh KTH Royal Institute of Technology, 2018 | 6 | 2018 |
Mårten BjörkmanAssociate Professor, KTH Royal Institute of TechnologyVerified email at kth.se
