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Bei Jiang — most-cited papers & profile · Reinforcement Learning
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overview
Bei Jiang
4
papers ·
1
citations
Google Scholar ↗
Semantic Scholar ↗
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Most-cited papers
Intrinsic Benefits of Categorical Distributional Loss: Uncertainty-aware Regularized Exploration in Reinforcement Learning
2021 · 1 citations
Distributional Reinforcement Learning with Regularized Wasserstein Loss
2022
The Sufficiency of Off-Policyness and Soft Clipping: PPO is still Insufficient according to an Off-Policy Measure
2022
How Does Return Distribution in Distributional Reinforcement Learning Help Optimization?
2022
Top co-authors
Linglong Kong
· 3
Ke Sun
· 2
Yingnan Zhao
· 2
Dongcui Diao
· 1
Enze Shi
· 1
Haiyin Piao
· 1
Hechang Chen
· 1
Hengshuai Yao
· 1
Ke Sun
· 1
Randy Goebel
· 1
Wulong Liu
· 1
Xiaodong Yan
· 1
Topics
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Exploration
Policy Gradient
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