Nicklas Hansen
Cited by
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Self-supervised policy adaptation during deployment
N Hansen, R Jangir, Y Sun, G Alenyà, P Abbeel, AA Efros, L Pinto, ...
arXiv preprint arXiv:2007.04309, 2020
Generalization in reinforcement learning by soft data augmentation
N Hansen, X Wang
2021 IEEE International Conference on Robotics and Automation (ICRA), 13611 …, 2021
Temporal difference learning for model predictive control
N Hansen, X Wang, H Su
Proceedings of the 39th International Conference on Machine Learning, PMLR …, 2022
Open x-embodiment: Robotic learning datasets and rt-x models
A Padalkar, A Pooley, A Jain, A Bewley, A Herzog, A Irpan, A Khazatsky, ...
arXiv preprint arXiv:2310.08864, 2023
Stabilizing deep q-learning with convnets and vision transformers under data augmentation
N Hansen, H Su, X Wang
Advances in neural information processing systems 34, 3680-3693, 2021
Learning vision-guided quadrupedal locomotion end-to-end with cross-modal transformers
R Yang, M Zhang, N Hansen, H Xu, X Wang
arXiv preprint arXiv:2107.03996, 2021
On pre-training for visuo-motor control: Revisiting a learning-from-scratch baseline
N Hansen, Z Yuan, Y Ze, T Mu, A Rajeswaran, H Su, H Xu, X Wang
arXiv preprint arXiv:2212.05749, 2022
Look closer: Bridging egocentric and third-person views with transformers for robotic manipulation
R Jangir, N Hansen, S Ghosal, M Jain, X Wang
IEEE Robotics and Automation Letters 7 (2), 3046-3053, 2022
Gnfactor: Multi-task real robot learning with generalizable neural feature fields
Y Ze, G Yan, YH Wu, A Macaluso, Y Ge, J Ye, N Hansen, LE Li, X Wang
Conference on Robot Learning, 284-301, 2023
Visual reinforcement learning with self-supervised 3d representations
Y Ze, N Hansen, Y Chen, M Jain, X Wang
IEEE Robotics and Automation Letters 8 (5), 2890-2897, 2023
Graph inverse reinforcement learning from diverse videos
S Kumar, J Zamora, N Hansen, R Jangir, X Wang
Conference on Robot Learning, 55-66, 2023
Modem: Accelerating visual model-based reinforcement learning with demonstrations
N Hansen, Y Lin, H Su, X Wang, V Kumar, A Rajeswaran
arXiv preprint arXiv:2212.05698, 2022
Short term blood glucose prediction based on continuous glucose monitoring data
A Mohebbi, AR Johansen, N Hansen, PE Christensen, JM Tarp, ...
2020 42nd Annual International Conference of the IEEE Engineering in …, 2020
Td-mpc2: Scalable, robust world models for continuous control
N Hansen, H Su, X Wang
arXiv preprint arXiv:2310.16828, 2023
Open X-Embodiment: Robotic learning datasets and RT-X models
OXE Collaboration, A Padalkar, A Pooley, A Jain, A Bewley, A Herzog, ...
CoRR, abs/2310.08864, 2023
Finetuning offline world models in the real world
Y Feng, N Hansen, Z Xiong, C Rajagopalan, X Wang
arXiv preprint arXiv:2310.16029, 2023
Open x-embodiment: Robotic learning datasets and RT-x models
Q Vuong, S Levine, HR Walke, K Pertsch, A Singh, R Doshi, C Xu, J Luo, ...
Towards Generalist Robots: Learning Paradigms for Scalable Skill Acquisition …, 2023
On the feasibility of cross-task transfer with model-based reinforcement learning
Y Xu, N Hansen, Z Wang, YC Chan, H Su, Z Tu
arXiv preprint arXiv:2210.10763, 2022
A Recipe for Unbounded Data Augmentation in Visual Reinforcement Learning
A Almuzairee, N Hansen, HI Christensen
arXiv preprint arXiv:2405.17416, 2024
MoDem-V2: Visuo-Motor World Models for Real-World Robot Manipulation
P Lancaster, N Hansen, A Rajeswaran, V Kumar
arXiv preprint arXiv:2309.14236, 2023
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