Open Access Helper

OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Improving Robustness via Risk Averse Distributional Reinforcement Learning
Rahul Singh, Qinsheng Zhang, Yongxin Chen
arXiv (Cornell University) (2020)
Open Access | Times Cited: 10

Showing 10 citing articles:

Risk-Averse Offline Reinforcement Learning
Núria Armengol Urpí, Sebastian Curi, Andreas Krause
arXiv (Cornell University) (2021)
Open Access | Times Cited: 17
Risk-Conditioned Distributional Soft Actor-Critic for Risk-Sensitive Navigation
Jinyoung Choi, Christopher R. Dance, Jungeun Kim, et al.
(2021), pp. 8337-8344
Open Access | Times Cited: 16
RL-VAEGAN: Adversarial defense for reinforcement learning agents via style transfer
Yueyue Hu, Shiliang Sun
Knowledge-Based Systems (2021) Vol. 221, pp. 106967-106967
Closed Access | Times Cited: 10
Adaptive CVaR Optimization for Dynamical Systems with Path Space Stochastic Search.
Ziyi Wang, Oswin So, Keuntaek Lee, et al.
arXiv (Cornell University) (2020)
Closed Access | Times Cited: 3
Safe Q-Learning Approaches for Human-in-Loop Reinforcement Learning
Swathi Veerabathraswamy, Nirav Bhatt
(2023), pp. 16-21
Closed Access | Times Cited: 1
Exploring the Robustness of Distributional Reinforcement Learning against Noisy State Observations.
Ke Sun, Yi Liu, Yingnan Zhao, et al.
arXiv (Cornell University) (2021)
Closed Access | Times Cited: 3
Distributional Actor-Critic Ensemble for Uncertainty-Aware Continuous Control
Takuya Kanazawa, Haiyan Wang, Chetan Gupta
2022 International Joint Conference on Neural Networks (IJCNN) (2022), pp. 1-10
Open Access | Times Cited: 2
Risk-Averse Offline Reinforcement Learning
Núria Armengol Urpí, Sebastian Curi, Andreas Krause
International Conference on Learning Representations (2021)
Closed Access | Times Cited: 2
Risk-sensitive MPCs with Deep Distributional Inverse RL for Autonomous Driving
Keuntaek Lee, David Isele, Evangelos A. Theodorou, et al.
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2022), pp. 7635-7642
Closed Access | Times Cited: 1
Uncertainty Quantification for Efficient and Risk-Sensitive Reinforcement Learning
Mohamed-Harith Ibrahim, S. Lecœuche, Jacques Boonært, et al.
2021 IEEE Symposium Series on Computational Intelligence (SSCI) (2023), pp. 1429-1434
Closed Access
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