1 code implementation • 4 Sep 2023 • Niccolò Anceschi, Augusto Fasano, Giovanni Rebaudo
The smoothing distribution of dynamic probit models with Gaussian state dynamics was recently proved to belong to the unified skew-normal family.
1 code implementation • 4 Sep 2023 • Augusto Fasano, Niccolò Anceschi, Beatrice Franzolini, Giovanni Rebaudo
Binary regression models represent a popular model-based approach for binary classification.
1 code implementation • 4 Sep 2023 • Augusto Fasano, Niccolò Anceschi, Beatrice Franzolini, Giovanni Rebaudo
Bayesian binary regression is a prosperous area of research due to the computational challenges encountered by currently available methods either for high-dimensional settings or large datasets, or both.
no code implementations • 1 Jun 2022 • Augusto Fasano, Giovanni Rebaudo, Niccolò Anceschi
This allows to obtain simplified expressions for the parameters of the posterior distribution and an alternative derivation for the variational algorithm that gives a novel understanding of the fundamental results in Fasano and Durante (2022) as well as computational advantages in our special settings.
no code implementations • 14 Jul 2020 • Augusto Fasano, Daniele Durante
Multinomial probit models are routinely-implemented representations for learning how the class probabilities of categorical response data change with p observed predictors.
2 code implementations • 15 Nov 2019 • Augusto Fasano, Daniele Durante, Giacomo Zanella
Modern methods for Bayesian regression beyond the Gaussian response setting are often computationally impractical or inaccurate in high dimensions.
Methodology Computation