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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
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Invited Discussion of 'Sparse Bayesian factor analysis when the number of factors is unknown' by Frühwirth-Schnatter S., Hosszejni D., and Freitas Lopes H
Antonio Canale, Lorenzo Schiavon, Federica Stolf
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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
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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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