Anpeng Wu - RankMe

45 papers A* 16Journal 27Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Causal Inference with Complex Treatments: A Survey. ACM Comput. Surv. Yingrong Wang, Haoxuan Li, Minqin Zhu, Anpeng Wu, Baohong Li, Keting Yin, Ruoxuan Xiong, Fei Wu, Kun Kuang
2026	—	`conf`	Continuous-Time Counterfactual Quantile Learning for Risk-Sensitive Policy Optimization. KDD (1) Yi He, Anpeng Wu, Ruoxuan Xiong, Yingrong Wang, Kun Kuang
2026	J	`jnl`	Journey to the Centre of Cluster: Harnessing Interior Nodes for A/B Testing under Network Interference. CoRR Qianyi Chen, Anpeng Wu, Bo Li, Lu Deng, Yong Wang
2026	A*	`conf`	Uplift Modeling with Delayed Feedback: Identifiability and Algorithms. AAAI Chunyuan Zheng, Anpeng Wu, Chuan Zhou, Taojun Hu, Qingying Chen, Hongyi Liu, Chenxi Li, Huiyou Jiang, Haoxuan Li, Zhouchen Lin
2025	A*	`conf`	Causal Graph Transformer for Treatment Effect Estimation Under Unknown Interference. ICLR Anpeng Wu, Haiyi Qiu, Zhengming Chen, Zijian Li, Ruoxuan Xiong, Fei Wu, Kun Zhang
2025	—	`conf`	Classifying Treatment Responders: Bounds and Algorithms. KDD (1) Anpeng Wu, Haoxuan Li, Chunyuan Zheng, Kun Kuang, Kun Zhang
2025	J	`jnl`	General Information Metrics for Improving AI Model Training Efficiency. CoRR Jianfeng Xu, Congcong Liu, Xiaoying Tan, Xiaojie Zhu, Anpeng Wu, Huan Wan, Weijun Kong, Chun Li, Hu Xu, Kun Kuang, Fei Wu
2025	J	`jnl`	General information metrics for improving AI model training efficiency. Artif. Intell. Rev. Jianfeng Xu, Congcong Liu, Xiaoying Tan, Xiaojie Zhu, Anpeng Wu, Huan Wan, Weijun Kong, Chun Li, Hu Xu, Kun Kuang, Fei Wu
2025	A*	`conf`	Generalizing Causal Effects from Randomized Controlled Trials to Target Populations across Diverse Environments. ICML Baohong Li, Yingrong Wang, Anpeng Wu, Ming Ma, Ruoxuan Xiong, Kun Kuang
2025	J	`jnl`	Instrumental Variables in Causal Inference and Machine Learning: A Survey. ACM Comput. Surv. Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Fei Wu
2025	A*	`conf`	Invariant Deep Uplift Modeling for Incentive Assignment in Online Marketing via Probability of Necessity and Sufficiency. ICML Zexu Sun, Qiyu Han, Hao Yang, Anpeng Wu, Minqin Zhu, Dugang Liu, Chen Ma, Yunpeng Weng, Xing Tang, Xiuqiang He
2025	J	`jnl`	Learning double balancing representation for heterogeneous dose-response curve estimation. Neural Networks Minqin Zhu, Anpeng Wu, Haoxuan Li, Ruoxuan Xiong, Bo Li, Fei Wu, Kun Kuang
2025	J	`jnl`	Networked Instrumental Variable for Treatment Effect Estimation With Unobserved Confounders. IEEE Trans. Knowl. Data Eng. Ziyu Zhao, Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Bo Li, Zhihua Wang, Fei Wu
2025	J	`jnl`	ReTimeCausal: EM-Augmented Additive Noise Models for Interpretable Causal Discovery in Irregular Time Series. CoRR Weihong Li, Anpeng Wu, Kun Kuang, Keting Yin
2025	A*	`conf`	Rethinking Causal Ranking: A Balanced Perspective on Uplift Model Evaluation. ICML Minqin Zhu, Zexu Sun, Ruoxuan Xiong, Anpeng Wu, Baohong Li, Caizhi Tang, Jun Zhou, Fei Wu, Kun Kuang
2025	J	`jnl`	Sequential Treatment Effect Estimation with Unmeasured Confounders. CoRR Yingrong Wang, Anpeng Wu, Baohong Li, Ziyang Xiao, Ruoxuan Xiong, Qing Han, Kun Kuang
2025	J	`jnl`	Should Bias Always be Eliminated? A Principled Framework to Use Data Bias for OOD Generation. CoRR Yan Li, Guangyi Chen, Yunlong Deng, Zijian Li, Zeyu Tang, Anpeng Wu, Kun Zhang
2024	A*	`conf`	A Generative Approach for Treatment Effect Estimation under Collider Bias: From an Out-of-Distribution Perspective. ICML Baohong Li, Haoxuan Li, Anpeng Wu, Minqin Zhu, Shiyuan Peng, Qingyu Cao, Kun Kuang
2024	J	`jnl`	Causal Inference with Complex Treatments: A Survey. CoRR Yingrong Wang, Haoxuan Li, Minqin Zhu, Anpeng Wu, Ruoxuan Xiong, Fei Wu, Kun Kuang
2024	J	`jnl`	Causality for Large Language Models. CoRR Anpeng Wu, Kun Kuang, Minqin Zhu, Yingrong Wang, Yujia Zheng, Kairong Han, Baohong Li, Guangyi Chen, Fei Wu, Kun Zhang
2024	A*	`conf`	Contrastive Balancing Representation Learning for Heterogeneous Dose-Response Curves Estimation. AAAI Minqin Zhu, Anpeng Wu, Haoxuan Li, Ruoxuan Xiong, Bo Li, Xiaoqing Yang, Xuan Qin, Peng Zhen, Jiecheng Guo, Fei Wu, Kun Kuang
2024	J	`jnl`	Contrastive Balancing Representation Learning for Heterogeneous Dose-Response Curves Estimation. CoRR Minqin Zhu, Anpeng Wu, Haoxuan Li, Ruoxuan Xiong, Bo Li, Xiaoqing Yang, Xuan Qin, Peng Zhen, Jiecheng Guo, Fei Wu, Kun Kuang
2024	J	`jnl`	Generalized Encouragement-Based Instrumental Variables for Counterfactual Regression. CoRR Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Xiangwei Chen, Zexu Sun, Fei Wu, Kun Zhang
2024	A*	`conf`	Learning Causal Relations from Subsampled Time Series with Two Time-Slices. ICML Anpeng Wu, Haoxuan Li, Kun Kuang, Keli Zhang, Fei Wu
2024	A*	`conf`	Learning Discrete Latent Variable Structures with Tensor Rank Conditions. NeurIPS Zhengming Chen, Ruichu Cai, Feng Xie, Jie Qiao, Anpeng Wu, Zijian Li, Zhifeng Hao, Kun Zhang
2024	J	`jnl`	Learning Discrete Latent Variable Structures with Tensor Rank Conditions. CoRR Zhengming Chen, Ruichu Cai, Feng Xie, Jie Qiao, Anpeng Wu, Zijian Li, Zhifeng Hao, Kun Zhang
2024	A*	`conf`	Learning Shadow Variable Representation for Treatment Effect Estimation under Collider Bias. ICML Baohong Li, Haoxuan Li, Ruoxuan Xiong, Anpeng Wu, Fei Wu, Kun Kuang
2024	J	`jnl`	Pareto-Optimal Estimation and Policy Learning on Short-term and Long-term Treatment Effects. CoRR Yingrong Wang, Anpeng Wu, Haoxuan Li, Weiming Liu, Qiaowei Miao, Ruoxuan Xiong, Fei Wu, Kun Kuang
2024	A*	`conf`	Stable Heterogeneous Treatment Effect Estimation across Out-of-Distribution Populations. ICDE Yuling Zhang, Anpeng Wu, Kun Kuang, Liang Du, Zixun Sun, Zhi Wang
2024	J	`jnl`	Stable Heterogeneous Treatment Effect Estimation across Out-of-Distribution Populations. CoRR Yuling Zhang, Anpeng Wu, Kun Kuang, Liang Du, Zixun Sun, Zhi Wang
2024	A*	`conf`	Two-Stage Shadow Inclusion Estimation: An IV Approach for Causal Inference under Latent Confounding and Collider Bias. ICML Baohong Li, Anpeng Wu, Ruoxuan Xiong, Kun Kuang
2023	J	`jnl`	Edge-Cloud Polarization and Collaboration: A Comprehensive Survey for AI. IEEE Trans. Knowl. Data Eng. 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
2023	J	`jnl`	Hierarchical Topological Ordering with Conditional Independence Test for Limited Time Series. CoRR Anpeng Wu, Haoxuan Li, Kun Kuang, Keli Zhang, Fei Wu
2023	J	`jnl`	Learning Decomposed Representations for Treatment Effect Estimation. IEEE Trans. Knowl. Data Eng. Anpeng Wu, Junkun Yuan, Kun Kuang, Bo Li, Runze Wu, Qiang Zhu, Yueting Zhuang, Fei Wu
2023	A*	`conf`	Learning Instrumental Variable from Data Fusion for Treatment Effect Estimation. AAAI Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Minqing Zhu, Yuxuan Liu, Bo Li, Furui Liu, Zhihua Wang, Fei Wu
2023	A*	`conf`	Stable Estimation of Heterogeneous Treatment Effects. ICML Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Bo Li, Fei Wu
2022	J	`jnl`	Auto IV: Counterfactual Prediction via Automatic Instrumental Variable Decomposition. ACM Trans. Knowl. Discov. Data Junkun Yuan, Anpeng Wu, Kun Kuang, Bo Li, Runze Wu, Fei Wu, Lanfen Lin
2022	J	`jnl`	Confounder Balancing for Instrumental Variable Regression with Latent Variable. CoRR Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Bo Li, Fei Wu
2022	A*	`conf`	Estimating Individualized Causal Effect with Confounded Instruments. KDD Haotian Wang, Wenjing Yang, Longqi Yang, Anpeng Wu, Liyang Xu, Jing Ren, Fei Wu, Kun Kuang
2022	A*	`conf`	Instrumental Variable Regression with Confounder Balancing. ICML Anpeng Wu, Kun Kuang, Bo Li, Fei Wu
2022	J	`jnl`	Instrumental Variables in Causal Inference and Machine Learning: A Survey. CoRR Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Fei Wu
2022	J	`jnl`	Treatment Effect Estimation with Unmeasured Confounders in Data Fusion. CoRR Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Minqing Zhu, Yuxuan Liu, Bo Li, Furui Liu, Zhihua Wang, Fei Wu
2021	J	`jnl`	Auto IV: Counterfactual Prediction via Automatic Instrumental Variable Decomposition. CoRR Junkun Yuan, Anpeng Wu, Kun Kuang, Bo Li, Runze Wu, Fei Wu, Lanfen Lin
2021	J	`jnl`	Edge-Cloud Polarization and Collaboration: A Comprehensive Survey. CoRR 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
2020	J	`jnl`	Learning Decomposed Representation for Counterfactual Inference. CoRR Anpeng Wu, Kun Kuang, Junkun Yuan, Bo Li, Pan Zhou, Jianrong Tao, Qiang Zhu, Yueting Zhuang, Fei Wu