50 citations · 69 across the 8 of their papers we have counts for
9 papers
Module-structured mixture factor models for molecular subtype discovery in transcriptomic data
Jinran Wu, Geoffrey J. McLachlan, Saumyadipta Pyne
High-throughput gene expression data exhibit high dimensionality, complex intergene dependence, and pronounced biological heterogeneity across samples, presenting major challenges…
Data-fusion using factor analysis and low-rank matrix completion
Daniel Ahfock, Saumyadipta Pyne, Geoffrey J. McLachlan
Data-fusion involves the integration of multiple related datasets. The statistical file-matching problem is a canonical data-fusion problem in multivariate analysis, where the obje…
AICov: An Integrative Deep Learning Framework for COVID-19 Forecasting with Population Covariates
Geoffrey C. Fox, Gregor von Laszewski, Fugang Wang +1
The COVID-19 pandemic has profound global consequences on health, economic, social, political, and almost every major aspect of human life. Therefore, it is of great importance to…
Clustering patterns connecting COVID-19 dynamics and Human mobility using optimal transport
Frank Nielsen, Gautier Marti, Sumanta Ray +1
Social distancing and stay-at-home are among the few measures that are known to be effective in checking the spread of a pandemic such as COVID-19 in a given population. The patter…
Estimation of Residential Radon Concentration in Pennsylvania Counties by Data Fusion
Xuze Zhang, Saumyadipta Pyne, Benjamin Kedem
A data fusion method for the estimation of residential radon level distribution in any Pennsylvania county is proposed. The method is based on a multi-sample density ratio model wi…
Statistical matching of non-Gaussian data
Daniel Ahfock, Saumyadipta Pyne, Geoffrey J. McLachlan
The statistical matching problem is a data integration problem with structured missing data. The general form involves the analysis of multiple datasets that only have a strict sub…