Saved in:
| Main Authors: | Zhang, Jiuchen, Zhou, Ling, Song, Peter |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2602.02172 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Cumulative Treatment Effect Testing under Continuous Time Reinforcement Learning
by: Zhang, Jiuchen, et al.
Published: (2026)
by: Zhang, Jiuchen, et al.
Published: (2026)
A Propagation Framework for Network Regression
by: Ma, Yingying, et al.
Published: (2026)
by: Ma, Yingying, et al.
Published: (2026)
Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics
by: Zhu, Haonan, et al.
Published: (2025)
by: Zhu, Haonan, et al.
Published: (2025)
High-Dimensional Expected Shortfall Regression
by: Zhang, Shushu, et al.
Published: (2023)
by: Zhang, Shushu, et al.
Published: (2023)
Exact Coordinate Descent for High-Dimensional Regularized Huber Regression
by: Kim, Younghoon, et al.
Published: (2025)
by: Kim, Younghoon, et al.
Published: (2025)
Deep Fréchet Regression
by: Iao, Su I, et al.
Published: (2024)
by: Iao, Su I, et al.
Published: (2024)
Bagged Polynomial Regression and Neural Networks
by: Klosin, Sylvia, et al.
Published: (2022)
by: Klosin, Sylvia, et al.
Published: (2022)
DFNN: A Deep Fréchet Neural Network Framework for Learning Metric-Space-Valued Responses
by: Kim, Kyum, et al.
Published: (2025)
by: Kim, Kyum, et al.
Published: (2025)
Individualized Dynamic Latent Factor Model for Multi-resolutional Data with Application to Mobile Health
by: Zhang, Jiuchen, et al.
Published: (2023)
by: Zhang, Jiuchen, et al.
Published: (2023)
Scalable Expectation Propagation for Mixed-Effects Regression
by: Zhou, Jackson, et al.
Published: (2024)
by: Zhou, Jackson, et al.
Published: (2024)
Deep Neural Networks Guided Ensemble Learning for Point Estimation
by: Zhan, Tianyu, et al.
Published: (2021)
by: Zhan, Tianyu, et al.
Published: (2021)
On Doubly Robust Inference for Double Machine Learning in Semiparametric Regression
by: Dukes, Oliver, et al.
Published: (2021)
by: Dukes, Oliver, et al.
Published: (2021)
Robust Variable Selection for High-dimensional Regression with Missing Data and Measurement Errors
by: Zhang, Zhenhao, et al.
Published: (2024)
by: Zhang, Zhenhao, et al.
Published: (2024)
Multi-Task Learning for High-Dimensional Regression with Many Weak Instruments
by: Zhang, Di, et al.
Published: (2025)
by: Zhang, Di, et al.
Published: (2025)
Transfer Learning Under High-Dimensional Network Convolutional Regression Model
by: Wang, Liyuan, et al.
Published: (2025)
by: Wang, Liyuan, et al.
Published: (2025)
Inference for Heterogeneous Treatment Effects with Efficient Instruments and Machine Learning
by: Scheidegger, Cyrill, et al.
Published: (2025)
by: Scheidegger, Cyrill, et al.
Published: (2025)
Network Structural Equation Models for Causal Mediation and Spillover Effects
by: Kundu, Ritoban, et al.
Published: (2024)
by: Kundu, Ritoban, et al.
Published: (2024)
Model-Assisted Causal Inference for the Treatment Effect on Recurrent Events in the Presence of Terminal Events
by: Huang, Yiyuan, et al.
Published: (2026)
by: Huang, Yiyuan, et al.
Published: (2026)
Uncovering All Highly Credible Binary Treatment Hierarchy Questions in Network Meta-Analysis
by: Daly, Caitlin H., et al.
Published: (2025)
by: Daly, Caitlin H., et al.
Published: (2025)
Neural Generative Distributional Regression
by: Chai, Jinhang, et al.
Published: (2026)
by: Chai, Jinhang, et al.
Published: (2026)
Machine-Learning-Assisted Comparison of Regression Functions
by: Yan, Jian, et al.
Published: (2025)
by: Yan, Jian, et al.
Published: (2025)
Treatment Effect Estimation with Observational Network Data using Machine Learning
by: Emmenegger, Corinne, et al.
Published: (2022)
by: Emmenegger, Corinne, et al.
Published: (2022)
Modified BART for Learning Heterogeneous Effects in Regression Discontinuity Designs
by: Alcantara, Rafael, et al.
Published: (2024)
by: Alcantara, Rafael, et al.
Published: (2024)
Calibration Prediction Interval for Non-parametric Regression and Neural Networks
by: Wu, Kejin, et al.
Published: (2025)
by: Wu, Kejin, et al.
Published: (2025)
Bayesian Kernel Machine Regression via Random Fourier Features for Estimating Joint Health Effects of Multiple Exposures
by: Zhang, Danlu, et al.
Published: (2025)
by: Zhang, Danlu, et al.
Published: (2025)
Cross-Semantic Transfer Learning for High-Dimensional Linear Regression
by: Jiang, Jiancheng, et al.
Published: (2025)
by: Jiang, Jiancheng, et al.
Published: (2025)
Generalized Rank Regression
by: Tu, Jiyuan, et al.
Published: (2026)
by: Tu, Jiyuan, et al.
Published: (2026)
Collapsible Kernel Machine Regression for Exposomic Analyses
by: McGee, Glen, et al.
Published: (2024)
by: McGee, Glen, et al.
Published: (2024)
Uncovering Treatment Effect Heterogeneity in Pragmatic Gerontology Trials
by: Li, Changjun, et al.
Published: (2025)
by: Li, Changjun, et al.
Published: (2025)
Spatial Deep Convolutional Neural Networks
by: Wang, Qi, et al.
Published: (2024)
by: Wang, Qi, et al.
Published: (2024)
High Dimensional Logistic Regression Under Network Dependence
by: Mukherjee, Somabha, et al.
Published: (2021)
by: Mukherjee, Somabha, et al.
Published: (2021)
Adjusting for Spatial Correlation in Machine and Deep Learning
by: Heaton, Matthew J., et al.
Published: (2024)
by: Heaton, Matthew J., et al.
Published: (2024)
Ridge Estimation of High Dimensional Two-Way Fixed Effect Regression
by: He, Junnan, et al.
Published: (2026)
by: He, Junnan, et al.
Published: (2026)
Transfer Learning for High Dimensional Robust Regression
by: Yuan, Xiaohui, et al.
Published: (2024)
by: Yuan, Xiaohui, et al.
Published: (2024)
Distributional Off-Policy Evaluation with Deep Quantile Process Regression
by: Kuang, Qi, et al.
Published: (2026)
by: Kuang, Qi, et al.
Published: (2026)
Mixture Conditional Regression with Ultrahigh Dimensional Text Data for Estimating Extralegal Factor Effects
by: Shi, Jiaxin, et al.
Published: (2023)
by: Shi, Jiaxin, et al.
Published: (2023)
Decomposing Network Influence: Social Influence Regression
by: Minhas, Shahryar, et al.
Published: (2017)
by: Minhas, Shahryar, et al.
Published: (2017)
Interpretable Deep Neural Network for Modeling Functional Surrogates
by: Jeon, Yeseul, et al.
Published: (2025)
by: Jeon, Yeseul, et al.
Published: (2025)
Residual Importance Weighted Transfer Learning For High-dimensional Linear Regression
by: Zhao, Junlong, et al.
Published: (2023)
by: Zhao, Junlong, et al.
Published: (2023)
Inference for Fréchet Regression
by: Song, Wookyeong, et al.
Published: (2026)
by: Song, Wookyeong, et al.
Published: (2026)
Similar Items
-
Cumulative Treatment Effect Testing under Continuous Time Reinforcement Learning
by: Zhang, Jiuchen, et al.
Published: (2026) -
A Propagation Framework for Network Regression
by: Ma, Yingying, et al.
Published: (2026) -
Deep Active Learning based Experimental Design to Uncover Synergistic Genetic Interactions for Host Targeted Therapeutics
by: Zhu, Haonan, et al.
Published: (2025) -
High-Dimensional Expected Shortfall Regression
by: Zhang, Shushu, et al.
Published: (2023) -
Exact Coordinate Descent for High-Dimensional Regularized Huber Regression
by: Kim, Younghoon, et al.
Published: (2025)