Saved in:
| Main Authors: | Wang, Yunfeng, Zhang, Zhiheng, Gao, Zijun |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2606.00847 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Causal Partial Identification via Conditional Optimal Transport
by: Lin, Sirui, et al.
Published: (2025)
by: Lin, Sirui, et al.
Published: (2025)
Tightening Causal Bounds via Covariate-Aware Optimal Transport
by: Lin, Sirui, et al.
Published: (2025)
by: Lin, Sirui, et al.
Published: (2025)
On Identification of Optimal Dynamic Treatment Regimes with Proxies of Hidden Confounders
by: Zhang, Jeffrey, et al.
Published: (2024)
by: Zhang, Jeffrey, et al.
Published: (2024)
Partial Identification of Policy-Relevant Treatment Effects with Instrumental Variables via Optimal Transport
by: Tan, Jiyuan, et al.
Published: (2026)
by: Tan, Jiyuan, et al.
Published: (2026)
Heterogeneous Quantile Treatment Effect Estimation for Longitudinal Data with High-Dimensional Confounding
by: Qiu, Zhixin, et al.
Published: (2025)
by: Qiu, Zhixin, et al.
Published: (2025)
Causal Representation Learning with Optimal Compression under Complex Treatments
by: Liang, Wanting, et al.
Published: (2026)
by: Liang, Wanting, et al.
Published: (2026)
Nonparametric Identification and Inference for Counterfactual Distributions with Confounding
by: Sun, Jianle, et al.
Published: (2026)
by: Sun, Jianle, et al.
Published: (2026)
Nonparametric Sensitivity Analysis for Unobserved Confounding with Survival Outcomes
by: Hu, Rui, et al.
Published: (2025)
by: Hu, Rui, et al.
Published: (2025)
Adjusting auxiliary variables under approximate neighborhood interference
by: Lu, Xin, et al.
Published: (2024)
by: Lu, Xin, et al.
Published: (2024)
Debiased Inverse Propensity Score Weighting for Estimation of Average Treatment Effects with High-Dimensional Confounders
by: Wang, Yuhao, et al.
Published: (2020)
by: Wang, Yuhao, et al.
Published: (2020)
Transporting Predictions via Double Machine Learning: Predicting Partially Unobserved Students' Outcomes
by: Bargagli-Stoffi, Falco J., et al.
Published: (2025)
by: Bargagli-Stoffi, Falco J., et al.
Published: (2025)
Optimization-based Sensitivity Analysis for Unmeasured Confounding using Partial Correlations
by: Freidling, Tobias, et al.
Published: (2022)
by: Freidling, Tobias, et al.
Published: (2022)
Forecasting Causal Effects of Future Interventions: Confounding and Transportability Issues
by: Forastiere, Laura, et al.
Published: (2024)
by: Forastiere, Laura, et al.
Published: (2024)
Trustworthy assessment of heterogeneous treatment effect estimator
by: Gao, Zijun
Published: (2024)
by: Gao, Zijun
Published: (2024)
Adaptive sample splitting for randomization tests
by: Zhang, Yao, et al.
Published: (2025)
by: Zhang, Yao, et al.
Published: (2025)
Optimal Decision Rules Under Partial Identification
by: Yata, Kohei
Published: (2021)
by: Yata, Kohei
Published: (2021)
Partial Identification under Stratified Randomization
by: Ferman, Bruno, et al.
Published: (2026)
by: Ferman, Bruno, et al.
Published: (2026)
Selective randomization inference for subgroup effects with continuous biomarkers
by: Gao, Zijun
Published: (2025)
by: Gao, Zijun
Published: (2025)
Quasi Instrumental Variable Methods for Stable Hidden Confounding and Binary Outcome
by: Liu, Zhonghua, et al.
Published: (2025)
by: Liu, Zhonghua, et al.
Published: (2025)
A Spectral Confounder Adjustment for Spatial Regression with Multiple Exposures and Outcomes
by: Prim, Shih-Ni, et al.
Published: (2025)
by: Prim, Shih-Ni, et al.
Published: (2025)
Estimation and Inference for Causal Explainability
by: Zhang, Weihan, et al.
Published: (2025)
by: Zhang, Weihan, et al.
Published: (2025)
Causal Effect Identification in LiNGAM Models with Latent Confounders
by: Tramontano, Daniele, et al.
Published: (2024)
by: Tramontano, Daniele, et al.
Published: (2024)
Identification of Average Causal Effects in Confounded Additive Noise Models
by: Elahi, Muhammad Qasim, et al.
Published: (2024)
by: Elahi, Muhammad Qasim, et al.
Published: (2024)
Simultaneous Change Point Detection and Identification for High Dimensional Linear Models
by: Liu, Bin, et al.
Published: (2024)
by: Liu, Bin, et al.
Published: (2024)
Auditing Fairness under Unobserved Confounding
by: Byun, Yewon, et al.
Published: (2024)
by: Byun, Yewon, et al.
Published: (2024)
Evaluating Treatment Benefit Predictors using Observational Data: Contending with Identification and Confounding Bias
by: Xia, Yuan, et al.
Published: (2024)
by: Xia, Yuan, et al.
Published: (2024)
Robust Estimation and Model Selection for the Controlled Directed Effect with Unmeasured Mediator-Outcome Confounders
by: Orihara, Shunichiro, et al.
Published: (2024)
by: Orihara, Shunichiro, et al.
Published: (2024)
A Differential Effect Approach to Partial Identification of Treatment Effects
by: Chen, Kan, et al.
Published: (2023)
by: Chen, Kan, et al.
Published: (2023)
Missingness-Adaptive Factor Identification in High-Dimensional Data
by: Zeng, Ping, et al.
Published: (2026)
by: Zeng, Ping, et al.
Published: (2026)
Identification and Estimation of Joint Potential Outcome Distributions from a Single Study
by: Shahn, Zach, et al.
Published: (2025)
by: Shahn, Zach, et al.
Published: (2025)
Individualized Causal Effects under Network Interference with Combinatorial Treatments
by: Lu, Yunping, et al.
Published: (2026)
by: Lu, Yunping, et al.
Published: (2026)
Optimal Network-Guided Covariate Selection for High-Dimensional Data Integration
by: Shen, Tao, et al.
Published: (2025)
by: Shen, Tao, et al.
Published: (2025)
Integrative Analysis of High-dimensional RCT and RWD Subject to Censoring and Hidden Confounding
by: Ye, Xin, et al.
Published: (2025)
by: Ye, Xin, et al.
Published: (2025)
High-Dimensional Covariate-Dependent Gaussian Graphical Models
by: Wang, Jiacheng, et al.
Published: (2025)
by: Wang, Jiacheng, et al.
Published: (2025)
A Non-parametric Direct Learning Approach to Heterogeneous Treatment Effect Estimation under Unmeasured Confounding
by: Zhang, Xinhai, et al.
Published: (2024)
by: Zhang, Xinhai, et al.
Published: (2024)
Model Form Identification in High-Dimensional Functional Linear Regressions
by: Guo, Xingche, et al.
Published: (2026)
by: Guo, Xingche, et al.
Published: (2026)
Bounds and Sensitivity Analysis of the Causal Effect Under Outcome-Independent MNAR Confounding
by: Peña, Jose M.
Published: (2024)
by: Peña, Jose M.
Published: (2024)
Discovering Causal Relationships using Proxy Variables under Unmeasured Confounding
by: Wu, Yong, et al.
Published: (2025)
by: Wu, Yong, et al.
Published: (2025)
Nonlinear Causal Discovery with Confounders
by: Li, Chunlin, et al.
Published: (2023)
by: Li, Chunlin, et al.
Published: (2023)
The Proximal Surrogate Index: Long-Term Treatment Effects under Unobserved Confounding
by: Hung, Ting-Chih, et al.
Published: (2026)
by: Hung, Ting-Chih, et al.
Published: (2026)
Similar Items
-
Causal Partial Identification via Conditional Optimal Transport
by: Lin, Sirui, et al.
Published: (2025) -
Tightening Causal Bounds via Covariate-Aware Optimal Transport
by: Lin, Sirui, et al.
Published: (2025) -
On Identification of Optimal Dynamic Treatment Regimes with Proxies of Hidden Confounders
by: Zhang, Jeffrey, et al.
Published: (2024) -
Partial Identification of Policy-Relevant Treatment Effects with Instrumental Variables via Optimal Transport
by: Tan, Jiyuan, et al.
Published: (2026) -
Heterogeneous Quantile Treatment Effect Estimation for Longitudinal Data with High-Dimensional Confounding
by: Qiu, Zhixin, et al.
Published: (2025)