Source Themes

Pathway-based Bayesian factor models for omics data
Lorenzo Mauri, Federica Stolf, Amy H. Herring, Cameron Miller, David B. Dunson
Cite Code arXiv
Identifiable sparse Bayesian factorizations via meta regression
Sparse Bayesian factor models provide an effective framework to learn low-rank dependence structures in high-dimensional data. Their …
Antonio Canale, Lorenzo Schiavon, Federica Stolf
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Bayesian adaptive Tucker decompositions for tensor factorization
Tucker tensor decomposition offers a more effective representation for multiway data compared to the widely used PARAFAC model. …
Federica Stolf, Antonio Canale
Cite Journal Code arXiv
Infinite joint species distribution models
Joint species distribution models are popular in ecology for modeling covariate effects on species occurrence, while characterizing …
Federica Stolf, David B. Dunson
Cite Journal arXiv
A hierarchical Bayesian non-asymptotic extreme value model for spatial data
Spatial maps of extreme precipitation are crucial in flood prevention. Withthe aim of producing maps of precipitation return levels, we …
Federica Stolf, Antonio Canale
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