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stat.ME2026
Overfitted high-dimensional matrix factorizations via adaptive spectral shrinkage
Lorenzo Mauri, David B. Dunson
Factor models are popular approaches for analyzing high-dimensional data to extract low-rank signals and estimate covariances. They decompose the covariance matrix as the sum of lo…
stat.ME2026
Pathway-based Bayesian factor models for 'omics data
Lorenzo Mauri, Federica Stolf, Amy H. Herring +2
Interpreting RNA-sequencing data requires identifying coordinated gene expression patterns that correspond to biological pathways. Standard factor models provide useful dimension r…