Nonlinear nonparametric mixed-effects models for unsupervised classification. - Laura Azzimonti; Francesca Ieva; Anna Maria Paganoni (Comput. Stat., 2013)

Mixed Finite Elements for Spatial Regression with PDE Penalization. - Laura Azzimonti; Fabio Nobile; Laura M. Sangalli; Piercesare Secchi (SIAM/ASA J. Uncertain. Quantification, 2014)

Hierarchical Multinomial-Dirichlet Model for the Estimation of Conditional Probability Tables. - Laura Azzimonti; Giorgio Corani; Marco Zaffalon (ICDM, 2017)

Hierarchical estimation of parameters in Bayesian networks. - Laura Azzimonti; Giorgio Corani; Marco Zaffalon (Comput. Stat. Data Anal., 2019)

Modeling spatially dependent functional data via regression with differential regularization. - Eleonora Arnone; Laura Azzimonti; Fabio Nobile; Laura M. Sangalli (J. Multivar. Anal., 2019)

Efficient feature selection using shrinkage estimators. - Konstantinos Sechidis; Laura Azzimonti; Adam Craig Pocock; Giorgio Corani; James Weatherall; Gavin Brown 001 (Mach. Learn., 2019)

Structure Learning from Related Data Sets with a Hierarchical Bayesian Score. - Laura Azzimonti; Giorgio Corani; Marco Scutari (PGM, 2020)

Correction to: Efficient feature selection using shrinkage estimators. - Konstantinos Sechidis; Laura Azzimonti; Adam Craig Pocock; Giorgio Corani; James Weatherall; Gavin Brown 001 (Mach. Learn., 2020)

Using Mixed-Effects Models to Learn Bayesian Networks from Related Data Sets. - Marco Scutari; Christopher Marquis; Laura Azzimonti (PGM, 2022)

Using Mixed-Effect Models to Learn Bayesian Networks from Related Data Sets. - Marco Scutari; Christopher Marquis; Laura Azzimonti (CoRR, 2022)

A Bayesian hierarchical score for structure learning from related data sets. - Laura Azzimonti; Giorgio Corani; Marco Scutari (Int. J. Approx. Reason., 2022)

A Computationally Efficient Deep Learning-Based Surrogate Model of Prediabetes Progression. - Lea Multerer; Stefano Toniolo; Sandra Mitrovic; Maria Concetta Palumbo; Alessandro Ravoni; Paolo Tieri; Marco Forgione; Laura Azzimonti (BIBM, 2024)

Global Outlier Detection in a Federated Learning Setting with Isolation Forest. - Daniele Malpetti; Laura Azzimonti (CoRR, 2024)

Flotta: a Secure and Flexible Spark-inspired Federated Learning Framework. - Claudio Bonesana; Daniele Malpetti; Sandra Mitrovic; Francesca Mangili; Laura Azzimonti (CoRR, 2024)

Counterfactual Inference Using Ordinary Differential Equations to Assess the Effect of Physical Activity on Type 2 Diabetes Onset. - Marta Lenatti; Marco Zaffalon; Alessandro Antonucci 001; Pierluigi Francesco De Paola; Lea Multerer; Maurizio Mongelli; Alessia Paglialonga; Laura Azzimonti (AIME (1), 2025)

Physics-Informed Neural Networks for Hidden Insulin Dynamics Estimation from Glucose Data. - Lea Multerer; Manuel Acquistapace; Marco Forgione; Laura Azzimonti (AIME (2), 2025)