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…
cs.LG2025
Fused Lasso Improves Accuracy of Co-occurrence Network Inference in Grouped Samples
Daniel Agyapong, Briana H. Beatty, Peter G. Kennedy +2
Co-occurrence network inference algorithms have significantly advanced our understanding of microbiome communities. However, these algorithms typically analyze microbial associatio…
cs.LG2023
Cross-Validation for Training and Testing Co-occurrence Network Inference Algorithms
Daniel Agyapong, Jeffrey Ryan Propster, Jane Marks +1
Microorganisms are found in almost every environment, including the soil, water, air, and inside other organisms, like animals and plants. While some microorganisms cause diseases,…