From the 1 of 7 linked papers with an AI index.
7 papers
Doubly Robust Functional Representation Learning for Longitudinal Causal Inference with Irregular Histories
Mengfei Ran, Yifeng Shen, Ruijie Guan
The paper introduces a method called Doubly Robust Functional Representation Learning (DR-FRL) that transforms irregular, time‑varying data into targeted representations for longit…
Semiparametric Inference for Causal Effects on Functional Outcomes
Junzhu Nie, Chengxiu Ling, Mengfei Ran
Difference-in-differences (DiD) is a cornerstone of causal inference, yet extending it to functional outcomes is not a routine scalar generalization; rather, it entails three funda…
Universal 2-Local Symmetry-Preserving Quantum Neural Networks for Fermionic Systems
Ge Yan, Kaisen Pan, Ruocheng Wang +3
Simulating quantum many-body systems represents a fundamental challenge where classical machine learning methods are severely bottlenecked by the exponential curse of dimensionalit…
Group-Sparse Smoothing for Longitudinal Models with Time-Varying Coefficients
Yu Lu, Tianni Zhang, Yuyao Wang +1
Longitudinal associations may vary over time, yet allowing every regression effect to be dynamic can inflate estimation variance and obscure interpretable structure. We develop tim…
Adaptive Penalized Doubly Robust Regression for Longitudinal Data
Yuyao Wang, Yu Lu, Tianni Zhang +1
Longitudinal data often involve heterogeneity, sparse signals, and contamination from response outliers or high-leverage observations especially in biomedical science. Existing met…
Block Empirical Likelihood Inference for Longitudinal Generalized Partially Linear Single-Index Models
Tianni Zhang, Yuyao Wang, Yu Lu +1
Generalized partially linear single-index models (GPLSIMs) provide a flexible and interpretable semiparametric framework for longitudinal outcomes by combining a low-dimensional pa…