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GRD: A Generative Approach for Interpretable Reward Redistribution in Reinforcement Learning.

Y. Zhang, Y. Du, B. Huang, Z. Wang, J. Wang, M. Fang, and M. Pechenizkiy. CoRR, (2023)

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Haishi Huang

Haowei Huang

Feiqing Huang

Zhida Huang

Ying Huang

Other publications of authors with the same name

Identification of Time-Dependent Causal Model: A Gaussian Process Treatment.B. Huang, K. Zhang, and B. Schölkopf. IJCAI, page 3561-3568. AAAI Press, (2015)Generalized Independent Noise Condition for Estimating Latent Variable Causal Graphs.F. Xie, R. Cai, B. Huang, C. Glymour, Z. Hao, and K. Zhang. NeurIPS, (2020)Domain Adaptation as a Problem of Inference on Graphical Models.K. Zhang, M. Gong, P. Stojanov, B. Huang, Q. Liu, and C. Glymour. NeurIPS, (2020)ACAMDA: Improving Data Efficiency in Reinforcement Learning through Guided Counterfactual Data Augmentation.Y. Sun, E. Wang, B. Huang, C. Lu, L. Feng, C. Sun, and K. Zhang. AAAI, page 15193-15201. AAAI Press, (2024)Causal Discovery with Mixed Linear and Nonlinear Additive Noise Models: A Scalable Approach.W. Liu, B. Huang, E. Gao, Q. Ke, H. Bondell, and M. Gong. CLeaR, volume 236 of Proceedings of Machine Learning Research, page 1237-1263. PMLR, (2024)A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables.X. Dong, B. Huang, I. Ng, X. Song, Y. Zheng, S. Jin, R. Legaspi, P. Spirtes, and K. Zhang. ICLR, OpenReview.net, (2024)Sample-Efficient Reinforcement Learning via Counterfactual-Based Data Augmentation.C. Lu, B. Huang, K. Wang, J. Hernández-Lobato, K. Zhang, and B. Schölkopf. CoRR, (2020)Weight-variant Latent Causal Models.Y. Liu, Z. Zhang, D. Gong, M. Gong, B. Huang, A. van den Hengel, K. Zhang, and J. Shi. CoRR, (2022)Causal-learn: Causal Discovery in Python.Y. Zheng, B. Huang, W. Chen, J. Ramsey, M. Gong, R. Cai, S. Shimizu, P. Spirtes, and K. Zhang. J. Mach. Learn. Res., (2024)Factored Adaptation for Non-Stationary Reinforcement Learning.F. Feng, B. Huang, K. Zhang, and S. Magliacane. NeurIPS, (2022)

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Disambiguation of "Huang, Biwei"

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GRD: A Generative Approach for Interpretable Reward Redistribution in Reinforcement Learning.

Please choose a person to relate this publication to

Haishi Huang

Haowei Huang

Feiqing Huang

Zhida Huang

Ying Huang

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Huang, Biwei"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML GRD: A Generative Approach for Interpretable Reward Redistribution in Reinforcement Learning.

Please choose a person to relate this publication to

Haishi Huang

Haowei Huang

Feiqing Huang

Zhida Huang

Ying Huang

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
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URL
DOI
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APA
Chicago
DIN 1505
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GRD: A Generative Approach for Interpretable Reward Redistribution in Reinforcement Learning.