Nicklas Hansen
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Self-supervised policy adaptation during deployment
N Hansen, R Jangir, Y Sun, G AlenyÓ, 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), 13611á…, 2021
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
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
Temporal difference learning for model predictive control
N Hansen, X Wang, H Su
arXiv preprint arXiv:2203.04955, 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 iná…, 2020
Visual reinforcement learning with self-supervised 3d representations
Y Ze, N Hansen, Y Chen, M Jain, X Wang
arXiv preprint arXiv:2210.07241, 2022
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
Graph inverse reinforcement learning from diverse videos
S Kumar, J Zamora, N Hansen, R Jangir, X Wang
arXiv preprint arXiv:2207.14299, 2022
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
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
Wildlife tracking methods
DS Morrant, JM Turner, MA Jensen, NA Hansen, DS Bower, G K÷rtner, ...
Wildlife Research in Australia: Practical and Applied Methods, 180, 2022
Graph Inverse Reinforcement Learning from Diverse Videos
SKJ Zamora, N Hansen, RJX Wang
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