Xu Shi | DeepAI

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Featured Co-authors

Tianxi Cai
45 publications
Shuo Chen
39 publications
Eric Tchetgen Tchetgen
39 publications
Edgar Dobriban
37 publications
Jintao Wang
32 publications
Jian Song
31 publications
Wang Miao
24 publications
Eric J. Tchetgen Tchetgen
22 publications
Yifan Cui
19 publications
Andrew Ying
15 publications
Peter X. K. Song
14 publications

∙ 04/10/2023

A Framework for Understanding Selection Bias in Real-World Healthcare Data

Using administrative patient-care data such as Electronic Health Records...

0 Ritoban Kundu, et al. ∙

∙ 03/06/2023

The Effect of Substance Use on Brain Ageing: A New Causal Inference Framework for Incomplete and Massive Phenomic Data

Although substance use is known to be associated with cognitive decline ...

0 Chixiang Chen, et al. ∙

∙ 02/13/2023

On the Doppler Squint Effect in OTFS Systems over Doubly-Dispersive Channels: Modeling and Evaluation

Extensive work has demonstrated the excellent performance of orthogonal ...

0 Xuehan Wang, et al. ∙

∙ 01/27/2023

Chirp-based Hierarchical Beam Training for Extremely Large-Scale Massive MIMO

XL-MIMO promises to provide ultrahigh data rates in Terahertz (THz) spec...

0 Xu Shi, et al. ∙

∙ 11/25/2022

Enhanced Tracking and Beamforming Codebook Design for Wideband Terahertz Massive MIMO System

True-time-delay (TTD) lines are recently applied inside Terahertz (THz) ...

0 Xu Shi, et al. ∙

∙ 10/07/2022

Hierarchical Codebook-based Beam Training for Extremely Large-Scale Massive MIMO

Extremely large-scale multiple-input multiple-output (XL-MIMO) promises ...

0 Xu Shi, et al. ∙

∙ 10/05/2022

Doubly Robust Proximal Synthetic Controls

To infer the treatment effect for a single treated unit using panel data...

0 Hongxiang Qiu, et al. ∙

∙ 10/02/2022

Data-driven Automated Negative Control Estimation (DANCE): Search for, Validation of, and Causal Inference with Negative Controls

Negative control variables are increasingly used to adjust for unmeasure...

0 Erich Kummerfeld, et al. ∙

∙ 08/02/2022

Doubly Robust Proximal Causal Inference under Confounded Outcome-Dependent Sampling

Unmeasured confounding and selection bias are often of concern in observ...

0 Kendrick Qijun Li, et al. ∙

∙ 04/02/2022

Collaborative causal inference with a distributed data-sharing management

Data sharing barriers are paramount challenges arising from multicenter ...

0 Mengtong Hu, et al. ∙

∙ 03/23/2022

Double Negative Control Inference in Test-Negative Design Studies of Vaccine Effectiveness

The test-negative design (TND) has become a standard approach to evaluat...

0 Kendrick Qijun Li, et al. ∙

∙ 11/26/2021

Online Causal Inference with Application to Near Real-Time Post-Market Vaccine Safety Surveillance

Streaming data routinely generated by mobile phones, social networks, e-...

0 Xu Shi, et al. ∙

∙ 10/03/2021

Data Integration in Causal Inference

Integrating data from multiple heterogeneous sources has become increasi...

0 Xu Shi, et al. ∙

∙ 09/15/2021

Proximal Causal Inference for Complex Longitudinal Studies

A standard assumption for causal inference about the joint effects of ti...

0 Andrew Ying, et al. ∙

∙ 08/31/2021

Theory for identification and Inference with Synthetic Controls: A Proximal Causal Inference Framework

Synthetic control methods are commonly used to estimate the treatment ef...

0 Xu Shi, et al. ∙

∙ 08/31/2021

Triple-Structured Compressive Sensing-based Channel Estimation for RIS-aided MU-MIMO Systems

Reconfigurable intelligent surface (RIS) has been recognized as a potent...

0 Xu Shi, et al. ∙

∙ 11/17/2020

Semiparametric proximal causal inference

Skepticism about the assumption of no unmeasured confounding, also known...

0 Yifan Cui, et al. ∙

∙ 11/12/2020

Patient Recruitment Using Electronic Health Records Under Selection Bias: a Two-phase Sampling Framework

Electronic health records (EHRs) are increasingly recognized as a cost-e...

0 Guanghao Zhang, et al. ∙

∙ 09/23/2020

An Introduction to Proximal Causal Learning

A standard assumption for causal inference from observational data is th...

0 Eric J. Tchetgen Tchetgen, et al. ∙

∙ 09/11/2020

A Selective Review of Negative Control Methods in Epidemiology

Purpose of Review: Negative controls are a powerful tool to detect and a...

0 Xu Shi, et al. ∙

∙ 10/12/2018

Spherical Regression under Mismatch Corruption with Application to Automated Knowledge Translation

Motivated by a series of applications in data integration, language tran...

0 Xu Shi, et al. ∙

∙ 08/18/2018

A general approach to detect gene (G)-environment (E) additive interaction leveraging G-E independence in case-control studies

It is increasingly of interest in statistical genetics to test for the p...

0 Eric J. Tchetgen Tchetgen, et al. ∙

∙ 08/14/2018

Multiply Robust Causal Inference With Double Negative Control Adjustment for Unmeasured Confounding

Unmeasured confounding is a threat to causal inference in observational ...

0 Xu Shi, et al. ∙

∙ 08/10/2018

Estimation of natural indirect effects robust to unmeasured confounding and mediator measurement error

The use of causal mediation analysis to evaluate the pathways by which a...

0 Isabel R. Fulcher, et al. ∙

∙ 04/04/2018

Clinical Concept Embeddings Learned from Massive Sources of Medical Data

Word embeddings have emerged as a popular approach to unsupervised learn...

0 Andrew L. Beam, et al. ∙