13 citations · 27 across the 9 of their papers we have counts for
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cs.LG2021★ 2 cited
Improving Context-Based Meta-Reinforcement Learning with Self-Supervised Trajectory Contrastive Learning
Bernie Wang, Simon Xu, Kurt Keutzer +2
Meta-reinforcement learning typically requires orders of magnitude more samples than single task reinforcement learning methods. This is because meta-training needs to deal with mo…
eess.IV2021★ 4 cited
Deep Symmetric Adaptation Network for Cross-modality Medical Image Segmentation
Xiaoting Han, Lei Qi, Qian Yu +4
Unsupervised domain adaptation (UDA) methods have shown their promising performance in the cross-modality medical image segmentation tasks. These typical methods usually utilize a…
cs.LG2021★ 2 cited
Reinforcement Learning with Latent Flow
Wenling Shang, Xiaofei Wang, Aravind Srinivas +4
Temporal information is essential to learning effective policies with Reinforcement Learning (RL). However, current state-of-the-art RL algorithms either assume that such informati…