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Karol Arndt
Karol Arndt
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Verified email at aalto.fi
Title
Cited by
Cited by
Year
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
932020
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
452019
DROPO: Sim-to-real transfer with offline domain randomization
G Tiboni, K Arndt, V Kyrki
Robotics and Autonomous Systems 166, 104432, 2023
132023
SafeAPT: Safe Simulation-to-Real Robot Learning Using Diverse Policies Learned in Simulation
R Kaushik, K Arndt, V Kyrki
IEEE Robotics and Automation Letters 7 (3), 6838-6845, 2022
92022
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
72021
Online vs. offline adaptive domain randomization benchmark
G Tiboni, K Arndt, G Averta, V Kyrki, T Tommasi
International Workshop on Human-Friendly Robotics, 158-173, 2022
32022
Affine transport for sim-to-real domain adaptation
A Mallasto, K Arndt, M Heinonen, S Kaski, V Kyrki
arXiv preprint arXiv:2105.11739, 2021
22021
Co-imitation: learning design and behaviour by imitation
C Rajani, K Arndt, D Blanco-Mulero, KS Luck, V Kyrki
Proceedings of the AAAI Conference on Artificial Intelligence 37 (5), 6200-6208, 2023
12023
Training and evaluation of deep policies using reinforcement learning and generative models
A Ghadirzadeh, P Poklukar, K Arndt, C Finn, V Kyrki, D Kragic, ...
The Journal of Machine Learning Research 23 (1), 7860-7896, 2022
12022
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
12021
Understanding deep neural networks through the lens of their non-linearity
Q Bouniot, I Redko, A Mallasto, C Laclau, K Arndt, O Struckmeier, ...
arXiv preprint arXiv:2310.11439, 2023
2023
Learning representations that are closed-form Monge mapping optimal with application to domain adaptation
O Struckmeier, I Redko, A Mallasto, K Arndt, M Heinonen, V Kyrki
Transactions on Machine Learning Research, 2023
2023
Beyond invariant representation learning: linearly alignable latent spaces for efficient closed-form domain adaptation
O Struckmeier, I Redko, A Mallasto, K Arndt, M Heinonen, V Kyrki
arXiv preprint arXiv:2305.07500, 2023
2023
Safe and efficient transfer of robot policies from simulation to the real world
K Arndt
Aalto University, 2023
2023
Dynamic flex compensation, coordinated hoist control, and anti-sway control for load handling machines
J Vihonen, MM Aref, P Vladimír, K Arndt, DB Mulero, V Kyrki, J Naskali, ...
US Patent App. 17/849,145, 2022
2022
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