3 papers
cs.LG2026
Understanding When Poisson Log-Normal Models Outperform Penalized Poisson Regression for Microbiome Count Data
Daniel Agyapong, Julien Chiquet, Jane Marks +1
Multivariate count models are often justified by their ability to capture latent dependence, but researchers receive little guidance on when this added structure improves on simple…
stat.ME2024
Evaluating Parameter Uncertainty in the Poisson Lognormal Model with Corrected Variational Estimators
Bastien Batardière, Julien Chiquet, Mahendra Mariadassou
Count data analysis is essential across diverse fields, from ecology and accident analysis to single-cell RNA sequencing (scRNA-seq) and metagenomics. While log transformations are…
math.OC2024
Importance sampling-based gradient method for dimension reduction in Poisson log-normal model
Bastien Batardière, Julien Chiquet, Joon Kwon +1
High-dimensional count data poses significant challenges for statistical analysis, necessitating effective methods that also preserve explainability. We focus on a low rank constra…