48 citations · 153 across the 26 of their papers we have counts for
7 papers · 1 filter
A Double Regression Method for Graphical Modeling of High-dimensional Nonlinear and Non-Gaussian Data
Siqi Liang, Faming Liang
Graphical models have long been studied in statistics as a tool for inferring conditional independence relationships among a large set of random variables. The most existing works…
A Langevinized Ensemble Kalman Filter for Large-Scale Static and Dynamic Learning
Peiyi Zhang, Qifan Song, Faming Liang
The Ensemble Kalman Filter (EnKF) has achieved great successes in data assimilation in atmospheric and oceanic sciences, but its failure in convergence to the right filtering distr…
Markov Neighborhood Regression for High-Dimensional Inference
Faming Liang, Jingnan Xue, Bochao Jia
This paper proposes an innovative method for constructing confidence intervals and assessing p-values in statistical inference for high-dimensional linear models. The proposed meth…
Learning Gene Regulatory Networks with High-Dimensional Heterogeneous Data
Bochao Jia, Faming Liang
The Gaussian graphical model is a widely used tool for learning gene regulatory networks with high-dimensional gene expression data. Most existing methods for Gaussian graphical mo…
Fast Bayesian Integrative Learning of Multiple Gene Regulatory Networks for Type 1 Diabetes
Bochao Jia, Faming Liang, the TEDDY Study Group
Motivated by the need to study the molecular mechanism underlying Type 1 Diabetes (T1D) with the gene expression data collected from both the patients and healthy controls at multi…
A Bayesian Mark Interaction Model for Analysis of Tumor Pathology Images
Qiwei Li, Xinlei Wang, Faming Liang +1
With the advance of imaging technology, digital pathology imaging of tumor tissue slides is becoming a routine clinical procedure for cancer diagnosis. This process produces massiv…