Anpeng Wu

According to our database, Anpeng Wu authored at least 16 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Contrastive Balancing Representation Learning for Heterogeneous Dose-Response Curves Estimation.

Minqin Zhu, Anpeng Wu, Haoxuan Li, Ruoxuan Xiong, Bo Li, Xiaoqing Yang, Xuan Qin, Peng Zhen, Jiecheng Guo, Fei Wu, Kun Kuang

CoRR, 2024

Pareto-Optimal Estimation and Policy Learning on Short-term and Long-term Treatment Effects.

Yingrong Wang, Anpeng Wu, Haoxuan Li, Weiming Liu, Qiaowei Miao, Ruoxuan Xiong, Fei Wu, Kun Kuang

CoRR, 2024

Contrastive Balancing Representation Learning for Heterogeneous Dose-Response Curves Estimation.

Minqin Zhu, Anpeng Wu, Haoxuan Li, Ruoxuan Xiong, Bo Li, Xiaoqing Yang, Xuan Qin, Peng Zhen, Jiecheng Guo, Fei Wu, Kun Kuang

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Edge-Cloud Polarization and Collaboration: A Comprehensive Survey for AI.

Jiangchao Yao, Shengyu Zhang, Yang Yao, Feng Wang, Jianxin Ma, Jianwei Zhang, Yunfei Chu, Luo Ji, Kunyang Jia, Tao Shen, Anpeng Wu, Fengda Zhang, Ziqi Tan, Kun Kuang, Chao Wu, Fei Wu, Jingren Zhou, Hongxia Yang

IEEE Trans. Knowl. Data Eng., July, 2023

Learning Decomposed Representations for Treatment Effect Estimation.

Anpeng Wu, Junkun Yuan, Kun Kuang, Bo Li, Runze Wu, Qiang Zhu, Yueting Zhuang, Fei Wu

IEEE Trans. Knowl. Data Eng., May, 2023

Hierarchical Topological Ordering with Conditional Independence Test for Limited Time Series.

Anpeng Wu, Haoxuan Li, Kun Kuang, Keli Zhang, Fei Wu

CoRR, 2023

Stable Estimation of Heterogeneous Treatment Effects.

Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Bo Li, Fei Wu

Proceedings of the International Conference on Machine Learning, 2023

Learning Instrumental Variable from Data Fusion for Treatment Effect Estimation.

Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Minqing Zhu, Yuxuan Liu, Bo Li, Furui Liu, Zhihua Wang, Fei Wu

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Auto IV: Counterfactual Prediction via Automatic Instrumental Variable Decomposition.

Junkun Yuan, Anpeng Wu, Kun Kuang, Bo Li, Runze Wu, Fei Wu, Lanfen Lin

ACM Trans. Knowl. Discov. Data, 2022

Instrumental Variables in Causal Inference and Machine Learning: A Survey.

Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Fei Wu

CoRR, 2022

Confounder Balancing for Instrumental Variable Regression with Latent Variable.

Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Bo Li, Fei Wu

CoRR, 2022

Treatment Effect Estimation with Unmeasured Confounders in Data Fusion.

Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Minqing Zhu, Yuxuan Liu, Bo Li, Furui Liu, Zhihua Wang, Fei Wu

CoRR, 2022

Estimating Individualized Causal Effect with Confounded Instruments.

Haotian Wang, Wenjing Yang, Longqi Yang, Anpeng Wu, Liyang Xu, Jing Ren, Fei Wu, Kun Kuang

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Instrumental Variable Regression with Confounder Balancing.

Anpeng Wu, Kun Kuang, Bo Li, Fei Wu

Proceedings of the International Conference on Machine Learning, 2022

2021

Edge-Cloud Polarization and Collaboration: A Comprehensive Survey.

Jiangchao Yao, Shengyu Zhang, Yang Yao, Feng Wang, Jianxin Ma, Jianwei Zhang, Yunfei Chu, Luo Ji, Kunyang Jia, Tao Shen, Anpeng Wu, Fengda Zhang, Ziqi Tan, Kun Kuang, Chao Wu, Fei Wu, Jingren Zhou, Hongxia Yang

CoRR, 2021

2020

Learning Decomposed Representation for Counterfactual Inference.

Anpeng Wu, Kun Kuang, Junkun Yuan, Bo Li, Pan Zhou, Jianrong Tao, Qiang Zhu, Yueting Zhuang, Fei Wu

CoRR, 2020