activity
20242026
collaborators

7 papers

stat.ME2026

Phylogenetic latent space models for network data

Federico Pavone, Daniele Durante, Robin J. Ryder

Latent space models for network data characterize each node through a vector of latent features whose pairwise similarities define the edge probabilities among the pairs of nodes.…

stat.AP2026

Low-rank bilinear autoregressive models for three-way criminal activity tensors

Gregor Zens, Carlos Díaz, Daniele Durante +1

Criminal activity data are typically available via a three-way tensor encoding the reported frequencies of different crime categories across time and space. The challenges that ari…

stat.ME2026

Skew-symmetric approximations of posterior distributions

Francesco Pozza, Daniele Durante, Botond Szabo

Popular deterministic approximations of posterior distributions from, e.g. the Laplace method, variational Bayes and expectation-propagation, generally rely on symmetric approximat…

stat.ML2025

Optimal and computationally tractable lower bounds for logistic log-likelihoods

Niccolò Anceschi, Cristian Castiglione, Tommaso Rigon +2

The logit transform is arguably the most widely-employed link function beyond linear settings. This transformation routinely appears in regression models for binary data and provid…

stat.AP2025

Dependent stochastic block models for age-indexed sequences of directed causes-of-death networks

Giovanni Romanò, Cristian Castiglione, Daniele Durante

Death events commonly arise from complex interactions among interrelated causes, formally classified in reporting practices as underlying and contributing. Leveraging information f…

stat.AP2025

Bayesian local clustering of age-period mortality surfaces across multiple countries

Giovanni Romanò, Emanuele Aliverti, Daniele Durante

Although traditional literature on mortality modeling has focused on single countries in isolation, recent contributions have progressively moved toward joint models for multiple c…