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Main Authors:	Li, Xingyu, Liu, Qing, Jiang, Tony, Xia, Hong Amy, Hobbs, Brian P., Wei, Peng
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Methodology
Online Access:	https://arxiv.org/abs/2505.17917
Tags:	Add Tag No Tags, Be the first to tag this record!

Unsupervised dense random survival forests identify interpretable patient profiles with heterogeneous treatment benefit
by: Li, Xingyu, et al.
Published: (2026)

Hybrid Meta-learners for Estimating Heterogeneous Treatment Effects
by: Liang, Zhongyuan, et al.
Published: (2025)

TERRA: A Transformer-Enabled Recursive R-learner for Longitudinal Heterogeneous Treatment Effect Estimation
by: Shi, Lei, et al.
Published: (2025)

Towards R-learner with Continuous Treatments
by: Zhang, Yichi, et al.
Published: (2022)

Improving Power in Randomized Controlled Trials with Time-to-Event Endpoints: A Risk-Free Approach
by: Zhou, Junyi, et al.
Published: (2026)

Adaptive Experiments Toward Learning Treatment Effect Heterogeneity
by: Wei, Waverly, et al.
Published: (2023)

Estimation of Treatment Effects based on Kernel Matching
by: Ding, Chong, et al.
Published: (2025)

Combining Incomplete Observational and Randomized Data for Heterogeneous Treatment Effects
by: Yao, Dong, et al.
Published: (2024)

LongBet: Heterogeneous Treatment Effect Estimation in Panel Data
by: Wang, Meijia, et al.
Published: (2024)

Using Individualized Treatment Effects to Assess Treatment Effect Heterogeneity
by: Sechidis, Konstantinos, et al.
Published: (2025)

Safe Individualized Treatment Rules with Controllable Harm Rates
by: Wu, Peng, et al.
Published: (2025)

Assessing Heterogeneity of Treatment Effects
by: Kaji, Tetsuya, et al.
Published: (2023)

Heterogeneous Treatment Effects and Causal Mechanisms
by: Fu, Jiawei, et al.
Published: (2024)

Joint Estimation of Marginal and Heterogeneous Treatment Effects
by: Wuethrich, Leticia, et al.
Published: (2026)

Evaluating and Testing for Actionable Treatment Effect Heterogeneity
by: Ashouri, Mahsa, et al.
Published: (2025)

On Weighted Orthogonal Learners for Heterogeneous Treatment Effects
by: Morzywolek, Pawel, et al.
Published: (2023)

Nonparametric Estimation of Mediation Effects with A General Treatment
by: Huang, Lukang, et al.
Published: (2022)

Flexible Functional Treatment Effect Estimation
by: Wang, Jiayi, et al.
Published: (2023)

Estimation and Inference for the Average Treatment Effect in a Score-Explained Heterogeneous Treatment Effect Model
by: Wibisono, Kevin Christian, et al.
Published: (2025)

Outlier-Resistant Heterogeneous Treatment Effect Estimation in HDLSS Settings via GAT--CVAE Framework
by: Lee, Byeonghee, et al.
Published: (2025)

Treatment Effect Heterogeneity and Importance Measures for Multivariate Continuous Treatments
by: Shin, Heejun, et al.
Published: (2024)

CURLS: Causal Rule Learning for Subgroups with Significant Treatment Effect
by: Zhou, Jiehui, et al.
Published: (2024)

Treatment Effect Heterogeneity in Regression Discontinuity Designs
by: Calonico, Sebastian, et al.
Published: (2025)

Estimating Treatment Effects Under Bounded Heterogeneity
by: Kwon, Soonwoo, et al.
Published: (2025)

The joint survival super learner: A super learner for right-censored data
by: Munch, Anders, et al.
Published: (2024)

Precision Mental Health: Predicting Heterogeneous Treatment Effects for Depression through Data Integration
by: Brantner, Carly L., et al.
Published: (2025)

A New Targeted-Federated Learning Framework for Estimating Heterogeneity of Treatment Effects: A Robust Framework with Applications in Aging Cohorts
by: Zhao, Rong, et al.
Published: (2025)

Semiparametric Estimation of Treatment Effects in Observational Studies with Heterogeneous Partial Interference
by: Qu, Zhaonan, et al.
Published: (2021)

Bayesian Causal Synthesis for Meta-Inference on Heterogeneous Treatment Effects
by: Sugasawa, Shonosuke, et al.
Published: (2023)

Estimating Heterogeneous Treatment Effects for Spatio-Temporal Causal Inference
by: Zhou, Lingxiao, et al.
Published: (2024)

Inference for Heterogeneous Treatment Effects with Efficient Instruments and Machine Learning
by: Scheidegger, Cyrill, et al.
Published: (2025)

Propensity Patchwork Kriging for Scalable Inference on Heterogeneous Treatment Effects
by: Ogawa, Hajime, et al.
Published: (2025)

Targeted Learning on Variable Importance Measure for Heterogeneous Treatment Effect
by: Li, Haodong, et al.
Published: (2023)

Uncovering Treatment Effect Heterogeneity in Pragmatic Gerontology Trials
by: Li, Changjun, et al.
Published: (2025)

Matching-Based Nonparametric Estimation of Group Average Treatment Effects
by: Wu, Peng, et al.
Published: (2025)

Estimating Effects of Longitudinal Modified Treatment Policies (LMTPs) on Rates of Change in Health Outcomes
by: Shahu, Anja, et al.
Published: (2025)

Spatial Interference Detection in Treatment Effect Model
by: Zhang, Wei, et al.
Published: (2024)

Assumption-Lean Differential Variance Inference for Heterogeneous Treatment Effect Detection
by: Boileau, Philippe A., et al.
Published: (2025)

Extention of Bagging MARS with Group LASSO for Heterogeneous Treatment Effect Estimation
by: He, Guanwenqing, et al.
Published: (2024)

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