:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Zhang, Jiuchen, Qu, Annie
Format:	Preprint
Published:	2026
Subjects:	Methodology
Online Access:	https://arxiv.org/abs/2602.02246
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Neural Network Machine Regression (NNMR): A Deep Learning Framework for Uncovering High-order Synergistic Effects
by: Zhang, Jiuchen, et al.
Published: (2026)

Individualized Dynamic Latent Factor Model for Multi-resolutional Data with Application to Mobile Health
by: Zhang, Jiuchen, et al.
Published: (2023)

Inference for Cumulative Incidences and Treatment Effects in Randomized Controlled Trials with Time-to-Event Outcomes under ICH E9 (R1)
by: Deng, Yuhao, et al.
Published: (2024)

Distributional Treatment Effect Estimation across Heterogeneous Sites via Optimal Transport
by: Bateni, Borna, et al.
Published: (2025)

Multi-Label Residual Weighted Learning for Individualized Combination Treatment Rule
by: Xu, Qi, et al.
Published: (2023)

Representation Retrieval Learning for Heterogeneous Data Integration
by: Xu, Qi, et al.
Published: (2025)

Two-Phase Treatment with Noncompliance: Identifying the Cumulative Average Treatment Effect via Multisite Instrumental Variables
by: Hong, Guanglei, et al.
Published: (2025)

Meta Fusion: A Unified Framework For Multimodality Fusion with Mutual Learning
by: Liang, Ziyi, et al.
Published: (2025)

Deep Learning of Continuous and Structured Policies for Aggregated Heterogeneous Treatment Effects
by: Zhang, Jennifer Y., et al.
Published: (2025)

Evaluating and Testing for Actionable Treatment Effect Heterogeneity
by: Ashouri, Mahsa, 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)

Individualized Causal Effects under Network Interference with Combinatorial Treatments
by: Lu, Yunping, et al.
Published: (2026)

Multi-task Learning for Heterogeneous Data via Integrating Shared and Task-Specific Encodings
by: Sui, Yang, et al.
Published: (2025)

Individualized Dynamic Mediation Analysis Using Latent Factor Models
by: Zhang, Yijiao, et al.
Published: (2024)

Double/Debiased Machine Learning for Continuous Treatment Effects in Panel Data with Endogeneity
by: Wu, Peikai, et al.
Published: (2026)

Designing Time Series Experiments in A/B Testing with Transformer Reinforcement Learning
by: Wu, Xiangkun, et al.
Published: (2026)

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

Longitudinal Generalizations of the Average Treatment Effect on the Treated for Multi-valued and Continuous Treatments
by: Susmann, Herbert, et al.
Published: (2024)

Capturing Cumulative Disease Burden in Chronic Kidney Disease Outcome Trials: Area Under the Curve and Restricted Mean Time in Favor of Treatment Beyond Conventional Time-to-First Analysis
by: Sun, Jiren, et al.
Published: (2026)

Nonparametric Estimation of Local Treatment Effects with Continuous Instruments
by: Zeng, Zhenghao, et al.
Published: (2025)

Efficient Estimation of Average Treatment Effect on the Treated under Endogenous Treatment Assignment
by: Ghosh, Trinetri, et al.
Published: (2023)

Reluctant Transfer Learning in Penalized Regressions for Individualized Treatment Rules under Effect Heterogeneity
by: Oh, Eun Jeong, et al.
Published: (2025)

Continuous Treatment Effects with Surrogate Outcomes
by: Zeng, Zhenghao, et al.
Published: (2024)

Incremental Causal Effect for Time to Treatment Initialization
by: Ying, Andrew, et al.
Published: (2024)

Double Machine Learning of Continuous Treatment Effects with General Instrumental Variables
by: Chen, Shuyuan, et al.
Published: (2026)

Sharp Bounds for Continuous-Valued Treatment Effects with Unobserved Confounders
by: Baitairian, Jean-Baptiste, et al.
Published: (2024)

Cumulative Marginal Mean Model for Assessing Sequential Effects Using Digital Health Data
by: Guo, Xingche, et al.
Published: (2025)

Covariate-Elaborated Robust Partial Information Transfer with Conditional Spike-and-Slab Prior
by: Zhang, Ruqian, et al.
Published: (2024)

Syntax-Guided Diffusion Language Models with User-Integrated Personalization
by: Zhang, Ruqian, et al.
Published: (2025)

Efficient Inference for Incremental Causal Effects of Time to Treatment
by: Zhao, Zhichen, et al.
Published: (2026)

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

Identification of Treatment Effects under Limited Exogenous Variation
by: Newey, Whitney K., et al.
Published: (2018)

Discrete Autoregressive Switching Processes with Cumulative Shrinkage Priors for Graphical Modeling of Time Series Data
by: Hadj-Amar, Beniamino, et al.
Published: (2024)

Group Sequential Testing of a Treatment Effect Using a Surrogate Marker
by: Parast, Layla, et al.
Published: (2024)

Partially-shared Imaging Regression on Integrating Heterogeneous Brain-Cognition Associations across Alzheimer's Diagnoses
by: Sui, Yang, et al.
Published: (2025)

Sharp Bounds for Treatment Effect Generalization under Outcome Distribution Shift
by: Asiaee, Amir, et al.
Published: (2026)

Estimating Causal Effects of Discrete and Continuous Treatments with Binary Instruments
by: Chernozhukov, Victor, et al.
Published: (2024)

Adaptive Bayesian Joint Latent Space Modeling via Cumulative Shrinkage
by: Lv, Bin, et al.
Published: (2025)

Adaptive Orthogonalization for Stable Estimation of the Effects of Time-Varying Treatments
by: Li, Yige, et al.
Published: (2025)

Dynamic Topic Modeling with a Higher-Order Hypergraphical Representation
by: Gao, Hanjia, et al.
Published: (2026)