| 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 | 38 | 2020 |
| 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 | 30 | 2019 |
| 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 |
| Domain Curiosity: Learning Efficient Data Collection Strategies for Domain Adaptation K Arndt, O Struckmeier, V Kyrki 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2021 | 1 | 2021 |
| 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 | | 2022 |
| SafeAPT: Safe Simulation-to-Real Robot Learning using Diverse Policies Learned in Simulation R Kaushik, K Arndt, V Kyrki arXiv preprint arXiv:2201.13248, 2022 | | 2022 |
| DROPO: Sim-to-Real Transfer with Offline Domain Randomization G Tiboni, K Arndt, V Kyrki arXiv preprint arXiv:2201.08434, 2022 | | 2022 |
| Affine Transport for Sim-to-Real Domain Adaptation A Mallasto, K Arndt, M Heinonen, S Kaski, V Kyrki arXiv preprint arXiv:2105.11739, 2021 | | 2021 |
Ville KyrkiAssociate Professor at Aalto UniversityVerified email at aalto.fi
