Towards Identifying Causal Relation Between Instances and Labels. - Tian-Zuo Wang; Sheng-Jun Huang; Zhi-Hua Zhou (SDM, 2019)

Cost-effectively Identifying Causal Effects When Only Response Variable is Observable. - Tian-Zuo Wang; Xi-Zhu Wu; Sheng-Jun Huang; Zhi-Hua Zhou (ICML, 2020)

Budgeted Heterogeneous Treatment Effect Estimation. - Tian Qin; Tian-Zuo Wang; Zhi-Hua Zhou (ICML, 2021)

Actively Identifying Causal Effects with Latent Variables Given Only Response Variable Observable. - Tian-Zuo Wang; Zhi-Hua Zhou (NeurIPS, 2021)

Estimating Possible Causal Effects with Latent Variables via Adjustment. - Tian-Zuo Wang; Tian Qin; Zhi-Hua Zhou (ICML, 2023)

Rehearsal Learning for Avoiding Undesired Future. - Tian Qin; Tian-Zuo Wang; Zhi-Hua Zhou (NeurIPS, 2023)

Learning Causal Structure on Mixed Data with Tree-Structured Functional Models. - Tian Qin; Tian-Zuo Wang; Zhi-Hua Zhou (SDM, 2023)

Sound and complete causal identification with latent variables given local background knowledge. - Tian-Zuo Wang; Tian Qin; Zhi-Hua Zhou (Artif. Intell., 2023)

An Efficient Maximal Ancestral Graph Listing Algorithm. - Tian-Zuo Wang; Wen-Bo Du 002; Zhi-Hua Zhou (ICML, 2024)

Avoiding Undesired Future with Minimal Cost in Non-Stationary Environments. - Wen-Bo Du 002; Tian Qin; Tian-Zuo Wang; Zhi-Hua Zhou (NeurIPS, 2024)

New Rules for Causal Identification with Background Knowledge. - Tian-Zuo Wang; Lue Tao; Zhi-Hua Zhou (CoRR, 2024)

Tracking treatment effect heterogeneity in evolving environments. - Tian Qin; Long-Fei Li; Tian-Zuo Wang; Zhi-Hua Zhou (Mach. Learn., 2024)

Gradient-Based Nonlinear Rehearsal Learning with Multivariate Alterations. - Tian Qin; Tian-Zuo Wang; Zhi-Hua Zhou (AAAI, 2025)

Estimating possible causal effects with latent variables via adjustment and novel rule orientation. - Tian-Zuo Wang; Lue Tao; Tian Qin; Zhi-Hua Zhou (Artif. Intell., 2025)

Gradient-based causal discovery with latent variables. - Haotian Ni; Tian-Zuo Wang; Hong Tao; Xiuqi Huang; Chenping Hou (Mach. Learn., 2025)