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Anpeng Wu

14 papers at tracked venues · 14 at CORE A* · active 2024–2026

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Venues

ICML ×7AAAI ×2SIGKDD ×2ICDE ×1ICLR ×1NeurIPS ×1

Frequent coauthors

Kun Kuang
×10
Ruoxuan Xiong
×7
Haoxuan Li
×6
Fei Wu
×5
Baohong Li
×5
Minqin Zhu
×4
Kun Zhang
×3
Yingrong Wang
×2
Chunyuan Zheng
×2
Zhengming Chen
×2
Zijian Li
×2
Zexu Sun
×2

Papers

  1. Continuous-Time Counterfactual Quantile Learning for Risk-Sensitive Policy Optimization
    SIGKDD 2026 ·
    Yi He
    , Anpeng Wu,
    Ruoxuan Xiong
    ,
    Yingrong Wang
    ,
    Kun Kuang
  2. Uplift Modeling with Delayed Feedback: Identifiability and Algorithms
    AAAI 2026 ·
    Chunyuan Zheng
    , Anpeng Wu,
    Chuan Zhou
    ,
    Taojun Hu
    ,
    Qingying Chen
    ,
    Hongyi Liu
    ,
    Chenxi Li
    ,
    Huiyou Jiang
    ,
    Haoxuan Li
    ,
    Zhouchen Lin
  3. Causal Graph Transformer for Treatment Effect Estimation Under Unknown Interference
    ICLR 2025 · Anpeng Wu,
    Haiyi Qiu
    ,
    Zhengming Chen
    ,
    Zijian Li
    ,
    Ruoxuan Xiong
    ,
    Fei Wu
    ,
    Kun Zhang
  4. Classifying Treatment Responders: Bounds and Algorithms
    SIGKDD 2025 · Anpeng Wu,
    Haoxuan Li
    ,
    Chunyuan Zheng
    ,
    Kun Kuang
    ,
    Kun Zhang
  5. Generalizing Causal Effects from Randomized Controlled Trials to Target Populations across Diverse Environments
    ICML 2025 ·
    Baohong Li
    ,
    Yingrong Wang
    , Anpeng Wu,
    Ming Ma
    ,
    Ruoxuan Xiong
    ,
    Kun Kuang
  6. Invariant Deep Uplift Modeling for Incentive Assignment in Online Marketing via Probability of Necessity and Sufficiency
    ICML 2025 ·
    Zexu Sun
    ,
    Qiyu Han
    ,
    Hao Yang
    , Anpeng Wu,
    Minqin Zhu
    ,
    Dugang Liu
    ,
    Chen Ma
    ,
    Yunpeng Weng
    ,
    Xing Tang
    ,
    Xiuqiang He
  7. Rethinking Causal Ranking: A Balanced Perspective on Uplift Model Evaluation
    ICML 2025 ·
    Minqin Zhu
    ,
    Zexu Sun
    ,
    Ruoxuan Xiong
    , Anpeng Wu,
    Baohong Li
    ,
    Caizhi Tang
    ,
    Jun Zhou
    ,
    Fei Wu
    ,
    Kun Kuang
  8. A Generative Approach for Treatment Effect Estimation under Collider Bias: From an Out-of-Distribution Perspective
    ICML 2024 ·
    Baohong Li
    ,
    Haoxuan Li
    , Anpeng Wu,
    Minqin Zhu
    ,
    Shiyuan Peng
    ,
    Qingyu Cao
    ,
    Kun Kuang
  9. Contrastive Balancing Representation Learning for Heterogeneous Dose-Response Curves Estimation
    AAAI 2024 ·
    Minqin Zhu
    , Anpeng Wu,
    Haoxuan Li
    ,
    Ruoxuan Xiong
    ,
    Bo Li
    ,
    Xiaoqing Yang
    ,
    Xuan Qin
    ,
    Peng Zhen
    ,
    Jiecheng Guo
    ,
    Fei Wu
    ,
    Kun Kuang
  10. Learning Causal Relations from Subsampled Time Series with Two Time-Slices
    ICML 2024 · Anpeng Wu,
    Haoxuan Li
    ,
    Kun Kuang
    ,
    Keli Zhang
    ,
    Fei Wu
  11. Learning Discrete Latent Variable Structures with Tensor Rank Conditions
    NeurIPS 2024 ·
    Zhengming Chen
    ,
    Ruichu Cai
    ,
    Feng Xie
    ,
    Jie Qiao
    , Anpeng Wu,
    Zijian Li
    ,
    Zhifeng Hao
    ,
    Kun Zhang
  12. Learning Shadow Variable Representation for Treatment Effect Estimation under Collider Bias
    ICML 2024 ·
    Baohong Li
    ,
    Haoxuan Li
    ,
    Ruoxuan Xiong
    , Anpeng Wu,
    Fei Wu
    ,
    Kun Kuang
  13. Stable Heterogeneous Treatment Effect Estimation across Out-of-Distribution Populations
    ICDE 2024 ·
    Yuling Zhang
    , Anpeng Wu,
    Kun Kuang
    ,
    Liang Du
    ,
    Zixun Sun
    ,
    Zhi Wang
  14. Two-Stage Shadow Inclusion Estimation: An IV Approach for Causal Inference under Latent Confounding and Collider Bias
    ICML 2024 ·
    Baohong Li
    , Anpeng Wu,
    Ruoxuan Xiong
    ,
    Kun Kuang