9 citations · 18 across the 8 of their papers we have counts for
4 papers · 1 filter
Multi-group Gaussian Processes
Didong Li, Andrew Jones, Sudipto Banerjee +1
Gaussian processes (GPs) are pervasive in functional data analysis, machine learning, and spatial statistics for modeling complex dependencies. Modern scientific data sets are typi…
Nonnegative spatial factorization
F. William Townes, Barbara E. Engelhardt
Gaussian processes are widely used for the analysis of spatial data due to their nonparametric flexibility and ability to quantify uncertainty, and recently developed scalable appr…
Active multi-fidelity Bayesian online changepoint detection
Gregory W. Gundersen, Diana Cai, Chuteng Zhou +2
Online algorithms for detecting changepoints, or abrupt shifts in the behavior of a time series, are often deployed with limited resources, e.g., to edge computing settings such as…
Contrastive latent variable modeling with application to case-control sequencing experiments
Andrew Jones, F. William Townes, Didong Li +1
High-throughput RNA-sequencing (RNA-seq) technologies are powerful tools for understanding cellular state. Often it is of interest to quantify and summarize changes in cell state t…