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Ali Ghadirzadeh
Ali Ghadirzadeh
Embark Studios
Verified email at embark-studios.com
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Cited by
Cited by
Year
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
158*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
1152020
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
782020
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
652019
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
602016
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
572018
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
522019
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
46*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
322021
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
312020
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
202020
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
142020
Fine-tuning Offline Policies with Optimistic Action Selection
MS Mark, A Ghadirzadeh, X Chen, C Finn
Deep Reinforcement Learning Workshop NeurIPS 2022, 2022
132022
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
132016
Back to the manifold: Recovering from out-of-distribution states
A Reichlin, GL Marchetti, H Yin, A Ghadirzadeh, D Kragic
2022 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2022
102022
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
92015
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
82021
Coordinating with a robot partner affects neural processing related to action monitoring
A Czeszumski, AL Gert, A Keshava, A Ghadirzadeh, T Kalthoff, ...
Frontiers in neurorobotics, 102, 2021
8*2021
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
82014
Bayesian meta-learning for few-shot policy adaptation across robotic platforms. In 2021 IEEE
A Ghadirzadeh, X Chen, P Poklukar, C Finn, M Björkman, D Kragic
RSJ International Conference on Intelligent Robots and Systems (IROS), 1274-1280, 0
7
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