4 papers
Gradient-Flow Optimization as Dynamic Random-Effects Inference: Testing and Early Stopping with Applications to Deep Learning
Minhao Yao, Ruoyu Wang, Xihong Lin +2
Gradient-flow optimization is usually viewed as an algorithmic procedure for minimizing empirical loss, with training duration selected by validation or heuristic early stopping ru…
Mendelian Randomization Methods for Causal Inference: Estimands, Identification and Inference
Minhao Yao, Anqi Wang, Xihao Li +1
Mendelian randomization (MR) has become an essential tool for causal inference in biomedical and public health research. By using genetic variants as instrumental variables, MR hel…
Constructive Instrumental Variable Identification and Inference with Many Weak Interaction Moments
Di Zhang, Minhao Yao, Zhonghua Liu +1
Instrumental variable methods are widely used for causal inference, but identification becomes especially challenging when instruments are weak and potentially invalid. These chall…
An Introduction to Causal Inference Methods with Multi-omics Data
Minhao Yao, Zhonghua Liu
Omics biomarkers play a pivotal role in personalized medicine by providing molecular-level insights into the etiology of diseases, guiding precise diagnostics, and facilitating tar…