Learning Decomposed Representation for Counterfactual Inference. - Anpeng Wu; Kun Kuang; Junkun Yuan; Bo Li 064; Pan Zhou; Jianrong Tao; Qiang Zhu; Yueting Zhuang; Fei Wu 001 (CoRR, 2020)

Edge-Cloud Polarization and Collaboration: A Comprehensive Survey. - Jiangchao Yao; Shengyu Zhang 001; Yang Yao; Feng Wang 072; Jianxin Ma; Jianwei Zhang 012; Yunfei Chu; Luo Ji; Kunyang Jia; Tao Shen 002; Anpeng Wu; Fengda Zhang; et al. (CoRR, 2021)

Instrumental Variable Regression with Confounder Balancing. - Anpeng Wu; Kun Kuang; Bo Li 064; Fei Wu 001 (ICML, 2022)

Estimating Individualized Causal Effect with Confounded Instruments. - Haotian Wang 001; Wenjing Yang 002; Longqi Yang; Anpeng Wu; Liyang Xu; Jing Ren; Fei Wu 001; Kun Kuang (KDD, 2022)

Treatment Effect Estimation with Unmeasured Confounders in Data Fusion. - Anpeng Wu; Kun Kuang; Ruoxuan Xiong; Minqing Zhu; Yuxuan Liu; Bo Li 064; Furui Liu; Zhihua Wang 008; Fei Wu 001 (CoRR, 2022)

Confounder Balancing for Instrumental Variable Regression with Latent Variable. - Anpeng Wu; Kun Kuang; Ruoxuan Xiong; Bo Li 064; Fei Wu 001 (CoRR, 2022)

Auto IV: Counterfactual Prediction via Automatic Instrumental Variable Decomposition. - Junkun Yuan; Anpeng Wu; Kun Kuang; Bo Li 064; Runze Wu 001; Fei Wu 001; Lanfen Lin (ACM Trans. Knowl. Discov. Data, 2022)

Learning Instrumental Variable from Data Fusion for Treatment Effect Estimation. - Anpeng Wu; Kun Kuang; Ruoxuan Xiong; Minqing Zhu; Yuxuan Liu; Bo Li 064; Furui Liu; Zhihua Wang 008; Fei Wu 001 (AAAI, 2023)

Stable Estimation of Heterogeneous Treatment Effects. - Anpeng Wu; Kun Kuang; Ruoxuan Xiong; Bo Li 064; Fei Wu 001 (ICML, 2023)

Hierarchical Topological Ordering with Conditional Independence Test for Limited Time Series. - Anpeng Wu; Haoxuan Li 001; Kun Kuang; Keli Zhang; Fei Wu 001 (CoRR, 2023)

Learning Decomposed Representations for Treatment Effect Estimation. - Anpeng Wu; Junkun Yuan; Kun Kuang; Bo Li 064; Runze Wu 001; Qiang Zhu; Yueting Zhuang; Fei Wu 001 (IEEE Trans. Knowl. Data Eng., 2023)

Edge-Cloud Polarization and Collaboration: A Comprehensive Survey for AI. - Jiangchao Yao; Shengyu Zhang 001; Yang Yao; Feng Wang 072; Jianxin Ma; Jianwei Zhang 012; Yunfei Chu; Luo Ji; Kunyang Jia; Tao Shen 002; Anpeng Wu; Fengda Zhang; et al. (IEEE Trans. Knowl. Data Eng., 2023)

Contrastive Balancing Representation Learning for Heterogeneous Dose-Response Curves Estimation. - Minqin Zhu; Anpeng Wu; Haoxuan Li 001; Ruoxuan Xiong; Bo Li 064; Xiaoqing Yang; Xuan Qin; Peng Zhen 001; Jiecheng Guo; Fei Wu 001; Kun Kuang (AAAI, 2024)

Stable Heterogeneous Treatment Effect Estimation across Out-of-Distribution Populations. - Yuling Zhang; Anpeng Wu; Kun Kuang; Liang Du; Zixun Sun; Zhi Wang (ICDE, 2024)

A Generative Approach for Treatment Effect Estimation under Collider Bias: From an Out-of-Distribution Perspective. - Baohong Li; Haoxuan Li 001; Anpeng Wu; Minqin Zhu; Shiyuan Peng; Qingyu Cao; Kun Kuang (ICML, 2024)

Learning Shadow Variable Representation for Treatment Effect Estimation under Collider Bias. - Baohong Li; Haoxuan Li 001; Ruoxuan Xiong; Anpeng Wu; Fei Wu 001; Kun Kuang (ICML, 2024)

Two-Stage Shadow Inclusion Estimation: An IV Approach for Causal Inference under Latent Confounding and Collider Bias. - Baohong Li; Anpeng Wu; Ruoxuan Xiong; Kun Kuang (ICML, 2024)

Learning Causal Relations from Subsampled Time Series with Two Time-Slices. - Anpeng Wu; Haoxuan Li 001; Kun Kuang; Keli Zhang; Fei Wu 001 (ICML, 2024)

Learning Discrete Latent Variable Structures with Tensor Rank Conditions. - Zhengming Chen; Ruichu Cai; Feng Xie 002; Jie Qiao; Anpeng Wu; Zijian Li 001; Zhifeng Hao; Kun Zhang 001 (NeurIPS, 2024)

Pareto-Optimal Estimation and Policy Learning on Short-term and Long-term Treatment Effects. - Yingrong Wang; Anpeng Wu; Haoxuan Li 001; Weiming Liu 005; Qiaowei Miao; Ruoxuan Xiong; Fei Wu 001; Kun Kuang (CoRR, 2024)

Causal Inference with Complex Treatments: A Survey. - Yingrong Wang; Haoxuan Li 001; Minqin Zhu; Anpeng Wu; Ruoxuan Xiong; Fei Wu 001; Kun Kuang (CoRR, 2024)

Generalized Encouragement-Based Instrumental Variables for Counterfactual Regression. - Anpeng Wu; Kun Kuang; Ruoxuan Xiong; Xiangwei Chen; Zexu Sun; Fei Wu 001; Kun Zhang 001 (CoRR, 2024)

Causality for Large Language Models. - Anpeng Wu; Kun Kuang; Minqin Zhu; Yingrong Wang; Yujia Zheng 001; Kairong Han; Baohong Li; Guangyi Chen 002; Fei Wu 001; Kun Zhang 001 (CoRR, 2024)

Causal Graph Transformer for Treatment Effect Estimation Under Unknown Interference. - Anpeng Wu; Haiyi Qiu; Zhengming Chen; Zijian Li 001; Ruoxuan Xiong; Fei Wu 001; Kun Zhang 001 (ICLR, 2025)

Classifying Treatment Responders: Bounds and Algorithms. - Anpeng Wu; Haoxuan Li 001; Chunyuan Zheng 001; Kun Kuang; Kun Zhang 001 (KDD (1), 2025)

Learning double balancing representation for heterogeneous dose-response curve estimation. - Minqin Zhu; Anpeng Wu; Haoxuan Li 001; Ruoxuan Xiong; Bo Li 064; Fei Wu 001; Kun Kuang (Neural Networks, 2025)

Networked Instrumental Variable for Treatment Effect Estimation With Unobserved Confounders. - Ziyu Zhao 001; Anpeng Wu; Kun Kuang; Ruoxuan Xiong; Bo Li 064; Zhihua Wang 008; Fei Wu 001 (IEEE Trans. Knowl. Data Eng., 2025)

Sequential Treatment Effect Estimation with Unmeasured Confounders. - Yingrong Wang; Anpeng Wu; Baohong Li; Ziyang Xiao; Ruoxuan Xiong; Qing Han; Kun Kuang (CoRR, 2025)

ReTimeCausal: EM-Augmented Additive Noise Models for Interpretable Causal Discovery in Irregular Time Series. - Weihong Li; Anpeng Wu; Kun Kuang; Keting Yin (CoRR, 2025)

Should Bias Always be Eliminated? A Principled Framework to Use Data Bias for OOD Generation. - Yan Li 099; Guangyi Chen 002; Yunlong Deng; Zijian Li 001; Zeyu Tang 002; Anpeng Wu; Kun Zhang 001 (CoRR, 2025)

General information metrics for improving AI model training efficiency. - Jianfeng Xu; Congcong Liu; Xiaoying Tan; Xiaojie Zhu; Anpeng Wu; Huan Wan; Weijun Kong; Chun Li; Hu Xu; Kun Kuang; Fei Wu 001 (Artif. Intell. Rev., 2025)

Instrumental Variables in Causal Inference and Machine Learning: A Survey. - Anpeng Wu; Kun Kuang; Ruoxuan Xiong; Fei Wu 001 (ACM Comput. Surv., 2025)