57 citations · 159 across the 36 of their papers we have counts for
4 papers · 1 filter
Bayesian Transfer Learning
Piotr M. Suder, Jason Xu, David B. Dunson
Transfer learning is a burgeoning concept in statistical machine learning that seeks to improve inference and/or predictive accuracy on a domain of interest by leveraging data from…
Inferring Covariance Structure from Multiple Data Sources via Subspace Factor Analysis
Noirrit Kiran Chandra, David B. Dunson, Jason Xu
Factor analysis provides a canonical framework for imposing lower-dimensional structure such as sparse covariance in high-dimensional data. High-dimensional data on the same set of…
Fast Computation of Branching Process Transition Probabilities via ADMM
Achal Awasthi, Jason Xu
Branching processes are a class of continuous-time Markov chains (CTMCs) prevalent for modeling stochastic population dynamics in ecology, biology, epidemiology, and many other fie…
Inferring HIV Transmission Patterns from Viral Deep-Sequence Data via Latent Typed Point Processes
Fan Bu, Joseph Kagaayi, Kate Grabowski +2
Viral deep-sequencing data play a crucial role toward understanding disease transmission network flows, because the higher resolution of these data compared to standard Sanger sequ…