Marco Scutari

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 34

Top Topics

Hybrid Algorithms

Cancer Patients

Structure Learning

Top Venues

Int. J. Approx. Reason.

Publications

Marco Scutari
Entropy and the Kullback-Leibler Divergence for Bayesian Networks: Computational Complexity and Efficient Implementation. Algorithms 17 (1) (2024)
Lorenzo Valleggi, Marco Scutari, Federico Mattia Stefanini
Learning Bayesian networks with heterogeneous agronomic data sets via mixed-effect models and hierarchical clustering. Eng. Appl. Artif. Intell. 131 (2024)
Alessio Zanga, Alice Bernasconi, Peter J. F. Lucas, Hanny Pijnenborg, Casper Reijnen, Marco Scutari, Fabio Stella
Causal Discovery with Missing Data in a Multicentric Clinical Study. AIME (2023)
Lorenzo Valleggi, Marco Scutari, Federico Mattia Stefanini
Learning Bayesian Networks with Heterogeneous Agronomic Data Sets via Mixed-Effect Models and Hierarchical Clustering. CoRR (2023)
Marco Scutari
fairml: A Statistician's Take on Fair Machine Learning Modelling. CoRR (2023)
Alice Bernasconi, Alessio Zanga, Peter J. F. Lucas, Marco Scutari, Fabio Stella
Towards a Transportable Causal Network Model Based on Observational Healthcare Data. CoRR (2023)
Alessandro Bregoli, Karin Rathsman, Marco Scutari, Fabio Stella, Søren Wengel Mogensen
Analyzing Complex Systems with Cascades Using Continuous-Time Bayesian Networks. CoRR (2023)
Alessandro Bregoli, Karin Rathsman, Marco Scutari, Fabio Stella, Søren Wengel Mogensen
Analyzing Complex Systems with Cascades Using Continuous-Time Bayesian Networks. TIME (2023)
Alessio Zanga, Alice Bernasconi, Peter J. F. Lucas, Hanny Pijnenborg, Casper Reijnen, Marco Scutari, Fabio Stella
Causal Discovery with Missing Data in a Multicentric Clinical Study. CoRR (2023)
Alessio Zanga, Alice Bernasconi, Peter J. F. Lucas, Hanny Pijnenborg, Casper Reijnen, Marco Scutari, Fabio Stella
Risk Assessment of Lymph Node Metastases in Endometrial Cancer Patients: A Causal Approach. CoRR (2023)
Alice Bernasconi, Alessio Zanga, Peter J. F. Lucas, Marco Scutari, Fabio Antonio Stella
Towards a Transportable Causal Network Model Based on Observational Healthcare Data. HC@AIxIA (2023)
Marco Scutari
Entropy and the Kullback-Leibler Divergence for Bayesian Networks: Computational Complexity and Efficient Implementation. CoRR (2023)
Alessio Zanga, Alice Bernasconi, Peter J. F. Lucas, Hanny Pijnenborg, Casper Reijnen, Marco Scutari, Fabio Stella
Risk Assessment of Lymph Node Metastasis in Endometrial Cancer Patients: A Causal Approach. HC@AIxIA (2022)
Matteo Delucchi, Georg R. Spinner, Marco Scutari, Philippe Bijlenga, Sandrine Morel, Christoph M. Friedrich, Reinhard Furrer, Sven Hirsch
Bayesian network analysis reveals the interplay of intracranial aneurysm rupture risk factors. Comput. Biol. Medicine 147 (2022)
Marco Scutari
Comments on: "Hybrid Semiparametric Bayesian Networks". CoRR (2022)
Marco Scutari, Christopher Marquis, Laura Azzimonti
Using Mixed-Effect Models to Learn Bayesian Networks from Related Data Sets. CoRR (2022)
Marco Scutari, Christopher Marquis, Laura Azzimonti
Using Mixed-Effects Models to Learn Bayesian Networks from Related Data Sets. PGM (2022)
Marco Scutari, Francesca Panero, Manuel Proissl
Achieving fairness with a simple ridge penalty. Stat. Comput. 32 (5) (2022)
Laura Azzimonti, Giorgio Corani, Marco Scutari
A Bayesian hierarchical score for structure learning from related data sets. Int. J. Approx. Reason. 142 (2022)
Tjebbe Bodewes, Marco Scutari
Learning Bayesian networks from incomplete data with the node-average likelihood. Int. J. Approx. Reason. 138 (2021)
Alessandro Bregoli, Marco Scutari, Fabio Stella
A constraint-based algorithm for the structural learning of continuous-time Bayesian networks. Int. J. Approx. Reason. 138 (2021)
Marco Scutari, Manuel Proissl
Achieving Fairness with a Simple Ridge Penalty. CoRR (2021)
Andrea Ruggieri, Francesco Stranieri, Fabio Stella, Marco Scutari
Hard and Soft EM in Bayesian Network Learning from Incomplete Data. CoRR (2020)
Andrea Ruggieri, Francesco Stranieri, Fabio Stella, Marco Scutari
Hard and Soft EM in Bayesian Network Learning from Incomplete Data. Algorithms 13 (12) (2020)
Alessandro Bregoli, Marco Scutari, Fabio Stella
Constraint-Based Learning for Continuous-Time Bayesian Networks. CoRR (2020)
Laura Azzimonti, Giorgio Corani, Marco Scutari
Structure Learning from Related Data Sets with a Hierarchical Bayesian Score. PGM (2020)
Alessandro Bregoli, Marco Scutari, Fabio Stella
Constraing-Based Learning for Continous-Time Bayesian Networks. PGM (2020)
Laura Azzimonti, Giorgio Corani, Marco Scutari
Structure Learning from Related Data Sets with a Hierarchical Bayesian Score. CoRR (2020)
Tjebbe Bodewes, Marco Scutari
Identifiability and Consistency of Bayesian Network Structure Learning from Incomplete Data. PGM (2020)
Marco Scutari, Catharina Elisabeth Graafland, José Manuel Gutiérrez
Who learns better Bayesian network structures: Accuracy and speed of structure learning algorithms. Int. J. Approx. Reason. 115 (2019)
Marco Scutari, Claudia Vitolo, Allan Tucker
Learning Bayesian networks from big data with greedy search: computational complexity and efficient implementation. Stat. Comput. 29 (5) (2019)
Marco Scutari, Catharina Elisabeth Graafland, José Manuel Gutiérrez
Who Learns Better Bayesian Network Structures: Constraint-Based, Score-based or Hybrid Algorithms? PGM (2018)
Marco Scutari
Dirichlet Bayesian Network Scores and the Maximum Entropy Principle. AMBN (2017)
Marco Scutari
An Empirical-Bayes Score for Discrete Bayesian Networks. Probabilistic Graphical Models (2016)
Marco Scutari
Bayesian Network Constraint-Based Structure Learning Algorithms: Parallel and Optimised Implementations in the bnlearn R Package. CoRR (2014)
Marco Scutari, Radhakrishnan Nagarajan
Identifying significant edges in graphical models of molecular networks. Artif. Intell. Medicine 57 (3) (2013)
Shweta S. Chavan, Michael A. Bauer, Marco Scutari, Radhakrishnan Nagarajan
NATbox: a network analysis toolbox in R. BMC Bioinform. 10 (S-11) (2009)