5 papers
Causal Path Analysis from Perturbational and Population-Scale Single-Cell Data with Multiscale Confounding and Measurement Error
Kwangmoon Park, Hongzhe Li
Single-cell perturbation experiments provide causal information on gene regulation, whereas population-scale single-cell studies characterize gene expression and phenotypes in huma…
Multicalibration Boosting: Theory, Convergence, and Transferability
Hanxuan Ye, Hongzhe Li
Multicalibration extends classical calibration by requiring predictions to be unbiased over a rich collection of functions, encompassing both prediction slices and subpopulations.…
Confounder-robust causal discovery and inference in Perturb-seq using proxy and instrumental variables
Kwangmoon Park, Hongzhe Li
Emerging single-cell technologies that combine CRISPR-based genetic perturbations with single-cell RNA sequencing, such as Perturb-seq, offer unprecedented opportunities to uncover…
Differential Density Analysis in Single-Cell Genomics Using Specially Designed Exponential Families
Hanxuan Ye, Zachary Qian, Hongzhe Li
Recent advances in high-resolution sequencing have paved the way for population-scale analysis in single-cell RNA-sequencing (scRNA-seq) data. scRNA-seq data, in particular, have p…
Multicalibration for Modeling Censored Survival Data with Universal Adaptability
Hanxuan Ye, Hongzhe Li
Traditional statistical and machine learning methods typically assume that the training and test data follow the same distribution. However, this assumption is frequently violated…