Marco Scutari

According to our database, Marco Scutari authored at least 32 papers between 2009 and 2024.

Collaborative distances:

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

2024

Entropy and the Kullback-Leibler Divergence for Bayesian Networks: Computational Complexity and Efficient Implementation.

Marco Scutari

Algorithms, 2024

2023

Learning Bayesian Networks with Heterogeneous Agronomic Data Sets via Mixed-Effect Models and Hierarchical Clustering.

Lorenzo Valleggi, Marco Scutari, Federico Mattia Stefanini

CoRR, 2023

Risk Assessment of Lymph Node Metastases in Endometrial Cancer Patients: A Causal Approach.

Alessio Zanga, Alice Bernasconi, Peter J. F. Lucas, Hanny Pijnenborg, Casper Reijnen, Marco Scutari, Fabio Stella

CoRR, 2023

fairml: A Statistician's Take on Fair Machine Learning Modelling.

Marco Scutari

CoRR, 2023

Analyzing Complex Systems with Cascades Using Continuous-Time Bayesian Networks.

Alessandro Bregoli, Karin Rathsman, Marco Scutari, Fabio Stella, Søren Wengel Mogensen

Proceedings of the 30th International Symposium on Temporal Representation and Reasoning, 2023

Causal Discovery with Missing Data in a Multicentric Clinical Study.

Alessio Zanga, Alice Bernasconi, Peter J. F. Lucas, Hanny Pijnenborg, Casper Reijnen, Marco Scutari, Fabio Stella

Proceedings of the Artificial Intelligence in Medicine, 2023

Towards a Transportable Causal Network Model Based on Observational Healthcare Data.

Alice Bernasconi, Alessio Zanga, Peter J. F. Lucas, Marco Scutari, Fabio Antonio Stella

Proceedings of the 2nd AIxIA Workshop on Artificial Intelligence For Healthcare (HC@AIxIA 2023) co-located with the 22nd International Conference of the Italian Association for Artificial Intelligence (AIxIA 2023), 2023

2022

Achieving fairness with a simple ridge penalty.

Marco Scutari, Francesca Panero, Manuel Proissl

Stat. Comput., 2022

A Bayesian hierarchical score for structure learning from related data sets.

Laura Azzimonti, Giorgio Corani, Marco Scutari

Int. J. Approx. Reason., 2022

Using Mixed-Effect Models to Learn Bayesian Networks from Related Data Sets.

Marco Scutari, Christopher Marquis, Laura Azzimonti

CoRR, 2022

Comments on: "Hybrid Semiparametric Bayesian Networks".

Marco Scutari

CoRR, 2022

Bayesian network analysis reveals the interplay of intracranial aneurysm rupture risk factors.

Matteo Delucchi, Georg Ralph Spinner, Marco Scutari, Philippe Bijlenga, Sandrine Morel, Christoph M. Friedrich, Reinhard Furrer, Sven Hirsch

Comput. Biol. Medicine, 2022

Using Mixed-Effects Models to Learn Bayesian Networks from Related Data Sets.

Marco Scutari, Christopher Marquis, Laura Azzimonti

Proceedings of the International Conference on Probabilistic Graphical Models, 2022

Risk Assessment of Lymph Node Metastasis in Endometrial Cancer Patients: A Causal Approach.

Alessio Zanga, Alice Bernasconi, Peter J. F. Lucas, Hanny Pijnenborg, Casper Reijnen, Marco Scutari, Fabio Stella

Proceedings of the 1st AIxIA Workshop on Artificial Intelligence For Healthcare (HC@AIxIA 2022) co-located with the 21st International Conference of the Italian Association for Artificial Intelligence (AIxIA 2022), 2022

2021

A constraint-based algorithm for the structural learning of continuous-time Bayesian networks.

Alessandro Bregoli, Marco Scutari, Fabio Stella

Int. J. Approx. Reason., 2021

Learning Bayesian networks from incomplete data with the node-average likelihood.

Tjebbe Bodewes, Marco Scutari

Int. J. Approx. Reason., 2021

Achieving Fairness with a Simple Ridge Penalty.

Marco Scutari, Manuel Proissl

CoRR, 2021

2020

Constraint-Based Learning for Continuous-Time Bayesian Networks.

Alessandro Bregoli, Marco Scutari, Fabio Stella

CoRR, 2020

Hard and Soft EM in Bayesian Network Learning from Incomplete Data.

Andrea Ruggieri, Francesco Stranieri, Fabio Stella, Marco Scutari

Algorithms, 2020

Constraing-Based Learning for Continous-Time Bayesian Networks.

Alessandro Bregoli, Marco Scutari, Fabio Stella

Proceedings of the International Conference on Probabilistic Graphical Models, 2020

Identifiability and Consistency of Bayesian Network Structure Learning from Incomplete Data.

Tjebbe Bodewes, Marco Scutari

Proceedings of the International Conference on Probabilistic Graphical Models, 2020

Structure Learning from Related Data Sets with a Hierarchical Bayesian Score.

Laura Azzimonti, Giorgio Corani, Marco Scutari

Proceedings of the International Conference on Probabilistic Graphical Models, 2020

2019

Learning Bayesian networks from big data with greedy search: computational complexity and efficient implementation.

Marco Scutari, Claudia Vitolo, Allan Tucker

Stat. Comput., 2019

Who learns better Bayesian network structures: Accuracy and speed of structure learning algorithms.

Marco Scutari, Catharina Elisabeth Graafland, José Manuel Gutiérrez

Int. J. Approx. Reason., 2019

2018

Who Learns Better Bayesian Network Structures: Constraint-Based, Score-based or Hybrid Algorithms?

Marco Scutari, Catharina Elisabeth Graafland, José Manuel Gutiérrez

Proceedings of the International Conference on Probabilistic Graphical Models, 2018

2017

Dirichlet Bayesian Network Scores and the Maximum Entropy Principle.

Marco Scutari

Proceedings of the 3rd Workshop on Advanced Methodologies for Bayesian Networks, 2017

2016

An Empirical-Bayes Score for Discrete Bayesian Networks.

Marco Scutari

Proceedings of the Probabilistic Graphical Models - Eighth International Conference, 2016

2015

Graphical Modelling in Genetics and Systems Biology.

Marco Scutari

Proceedings of the Foundations of Biomedical Knowledge Representation, 2015

Personalised Medicine: Taking a New Look at the Patient.

Marco Scutari

Proceedings of the Foundations of Biomedical Knowledge Representation, 2015

2014

Bayesian Network Constraint-Based Structure Learning Algorithms: Parallel and Optimised Implementations in the bnlearn R Package.

Marco Scutari

CoRR, 2014

2013

Identifying significant edges in graphical models of molecular networks.

Marco Scutari, Radhakrishnan Nagarajan

Artif. Intell. Medicine, 2013

2009

NATbox: a network analysis toolbox in R.

Shweta S. Chavan, Michael A. Bauer, Marco Scutari, Radhakrishnan Nagarajan

BMC Bioinform., 2009