2 papers
stat.ME2024
Bayesian Adaptive Tucker Decompositions for Tensor Factorization
Federica Stolf, Antonio Canale
Tucker tensor decomposition offers a more effective representation for multiway data compared to the widely used PARAFAC model. However, its flexibility brings the challenge of sel…
stat.ME2022
A hierarchical Bayesian non-asymptotic extreme value model for spatial data
Federica Stolf, Antonio Canale
Spatial maps of extreme precipitation are crucial in flood protection. With the aim of producing maps of precipitation return levels, we propose a novel approach to model a collect…