activity
20242026
collaborators

6 papers

stat.ME2026

Adaptive discovery of effect modification in matched observational studies

Yu Gui, Dylan S Small, Zhimei Ren

Understanding effect modification -- how treatment effects vary across subpopulations -- is practically important in observational studies, as it helps identify which subgroups are…

econ.TH2026

Statistical Equilibrium of Optimistic Beliefs

Yu Gui, Bahar Taşkesen

We study finite normal-form games in which payoffs are subject to random perturbations and players face uncertainty about how these shocks co-move across actions, an ambiguity that…

stat.ML2025

IndiSeek learns information-guided disentangled representations

Yu Gui, Cong Ma, Zongming Ma

Learning disentangled representations is a fundamental task in multi-modal learning. In modern applications such as single-cell multi-omics, both shared and modality-specific featu…

stat.ML2025

Multi-modal contrastive learning adapts to intrinsic dimensions of shared latent variables

Yu Gui, Cong Ma, Zongming Ma

Multi-modal contrastive learning as a self-supervised representation learning technique has achieved great success in foundation model training, such as CLIP~\citep{radford2021lear…

cs.LG2025

Conformal Prediction: A Data Perspective

Xiaofan Zhou, Baiting Chen, Yu Gui +1

Conformal prediction (CP), a distribution-free uncertainty quantification (UQ) framework, reliably provides valid predictive inference for black-box models. CP constructs predictio…

stat.ME2024

Distributionally robust risk evaluation with an isotonic constraint

Yu Gui, Rina Foygel Barber, Cong Ma

Statistical learning under distribution shift is challenging when neither prior knowledge nor fully accessible data from the target distribution is available. Distributionally robu…