14 citations · 33 across the 6 of their papers we have counts for
6 papers
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…
Compositional Q-learning for electrolyte repletion with imbalanced patient sub-populations
Aishwarya Mandyam, Andrew Jones, Jiayu Yao +2
Reinforcement learning (RL) is an effective framework for solving sequential decision-making tasks. However, applying RL methods in medical care settings is challenging in part due…
Spectral embedding for dynamic networks with stability guarantees
Ian Gallagher, Andrew Jones, Patrick Rubin-Delanchy
We consider the problem of embedding a dynamic network, to obtain time-evolving vector representations of each node, which can then be used to describe changes in behaviour of indi…
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…
Probabilistic Contrastive Principal Component Analysis
Didong Li, Andrew Jones, Barbara Engelhardt
Dimension reduction is useful for exploratory data analysis. In many applications, it is of interest to discover variation that is enriched in a "foreground" dataset relative to a…
The multilayer random dot product graph
Andrew Jones, Patrick Rubin-Delanchy
We present a comprehensive extension of the latent position network model known as the random dot product graph to accommodate multiple graphs -- both undirected and directed -- wh…