Andrea Cappozzo

According to our database, Andrea Cappozzo authored at least 12 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

DISARM++: Beyond scanner-free harmonization.

Luca Caldera, Lara Cavinato, Alessio Cirone, Isabella Cama, Sara Garbarino, Raffaele Lodi, Fabrizio Tagliavini, Anna Nigri, Silvia De Francesco, Andrea Cappozzo, Michele Piana, Francesca Ieva

CoRR, May, 2025

Scoring probability maps in the basketball court with Indicator Kriging estimation.

Mirko Luigi Carlesso, Andrea Cappozzo, Marica Manisera, Paola Zuccolotto

Comput. Stat., April, 2025

Model-based clustering for covariance matrices via penalized Wishart mixture models.

Andrea Cappozzo, Alessandro Casa

Comput. Stat. Data Anal., 2025

2024

Variational inference for semiparametric Bayesian novelty detection in large datasets.

Luca Benedetti, Eric Boniardi, Leonardo Chiani, Jacopo Ghirri, Marta Mastropietro, Andrea Cappozzo, Francesco Denti

Adv. Data Anal. Classif., September, 2024

DISARM: Disentangled Scanner-Free Image Generation via Unsupervised Image2Image Translation.

Luca Caldera, Lara Cavinato, Andrea Cappozzo, Isabella Cama, Sara Garbarino, Alessio Cirone, Raffaele Lodi, Fabrizio Tagliavini, Anna Nigri, Silvia De Francesco, Francesca Ieva, RIN-Neuroimaging Network

Proceedings of the Machine Learning in Clinical Neuroimaging - 7th International Workshop, 2024

2023

Graphical and Computational Tools to Guide Parameter Choice for the Cluster Weighted Robust Model.

Andrea Cappozzo, Luis Angel García-Escudero, Francesca Greselin, Agustín Mayo-Íscar

J. Comput. Graph. Stat., 2023

2022

Correction to: A two-stage Bayesian semiparametricmodel for novelty detection with robust prior information.

Francesco Denti, Andrea Cappozzo, Francesca Greselin

Stat. Comput., 2022

Group-Wise Shrinkage Estimation in Penalized Model-Based Clustering.

Alessandro Casa, Andrea Cappozzo, Michael Fop

J. Classif., 2022

2021

A two-stage Bayesian semiparametric model for novelty detection with robust prior information.

Francesco Denti, Andrea Cappozzo, Francesca Greselin

Stat. Comput., 2021

Robust variable selection for model-based learning in presence of adulteration.

Andrea Cappozzo, Francesca Greselin, Thomas Brendan Murphy

Comput. Stat. Data Anal., 2021

2020

Anomaly and Novelty detection for robust semi-supervised learning.

Andrea Cappozzo, Francesca Greselin, Thomas Brendan Murphy

Stat. Comput., September, 2020

A robust approach to model-based classification based on trimming and constraints.

Andrea Cappozzo, Francesca Greselin, Thomas Brendan Murphy

Adv. Data Anal. Classif., 2020