13 citations · 72 across the 18 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…
From the Greene--Wu Convolution to Gradient Estimation over Riemannian Manifolds
Tianyu Wang, Yifeng Huang, Didong Li
Over a complete Riemannian manifold of finite dimension, Greene and Wu introduced a convolution, known as Greene-Wu (GW) convolution. In this paper, we study properties of the GW c…
Inference for Gaussian Processes with Matérn Covariogram on Compact Riemannian Manifolds
Didong Li, Wenpin Tang, Sudipto Banerjee
Gaussian processes are widely employed as versatile modelling and predictive tools in spatial statistics, functional data analysis, computer modelling and diverse applications of m…
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…