Marco Scutari | DeepAI

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∙ 08/21/2023

Analyzing Complex Systems with Cascades Using Continuous-Time Bayesian Networks

Interacting systems of events may exhibit cascading behavior where event...

0 Alessandro Bregoli, et al. ∙

∙ 08/11/2023

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

Research involving diverse but related data sets, where associations bet...

0 Lorenzo Valleggi, et al. ∙

∙ 05/17/2023

Causal Discovery with Missing Data in a Multicentric Clinical Study

Causal inference for testing clinical hypotheses from observational data...

0 Alessio Zanga, et al. ∙

∙ 05/17/2023

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

Assessing the pre-operative risk of lymph node metastases in endometrial...

0 Alessio Zanga, et al. ∙

∙ 05/03/2023

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

The adoption of machine learning in applications where it is crucial to ...

0 Marco Scutari, et al. ∙

∙ 06/08/2022

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

We commonly assume that data are a homogeneous set of observations when ...

0 Marco Scutari, et al. ∙

∙ 05/12/2022

Comments on: "Hybrid Semiparametric Bayesian Networks"

Invited discussion on the paper "Hybrid Semiparametric Bayesian Networks...

0 Marco Scutari, et al. ∙

∙ 05/18/2021

Achieving Fairness with a Simple Ridge Penalty

Estimating a fair linear regression model subject to a user-defined leve...

0 Marco Scutari, et al. ∙

∙ 12/09/2020

Hard and Soft EM in Bayesian Network Learning from Incomplete Data

Incomplete data are a common feature in many domains, from clinical tria...

11 Andrea Ruggieri, et al. ∙

∙ 08/04/2020

Structure Learning from Related Data Sets with a Hierarchical Bayesian Score

Score functions for learning the structure of Bayesian networks in the l...

0 Laura Azzimonti, et al. ∙

∙ 07/07/2020

Constraint-Based Learning for Continuous-Time Bayesian Networks

Dynamic Bayesian networks have been well explored in the literature as d...

0 Alessandro Bregoli, et al. ∙

∙ 04/29/2020

Identifiability and Consistency of Bayesian Network Structure Learning from Incomplete Data

Bayesian network (BN) structure learning from complete data has been ext...

0 Tjebbe Bodewes, et al. ∙

∙ 06/15/2019

From Incomplete, Dynamic Data to Bayesian Networks

Bayesian networks are a versatile and powerful tool to model complex phe...

0 Marco Scutari, et al. ∙

∙ 05/30/2018

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

The literature groups algorithms to learn the structure of Bayesian netw...

0 Marco Scutari, et al. ∙

∙ 04/22/2018

Learning Bayesian Networks from Big Data with Greedy Search: Computational Complexity and Efficient Implementation

Learning the structure of Bayesian networks from data is known to be a c...

0 Marco Scutari, et al. ∙

∙ 08/02/2017

Dirichlet Bayesian Network Scores and the Maximum Entropy Principle

A classic approach for learning Bayesian networks from data is to select...

0 Marco Scutari, et al. ∙

∙ 04/12/2017

Beyond Uniform Priors in Bayesian Network Structure Learning

Bayesian network structure learning is often performed in a Bayesian set...

0 Marco Scutari, et al. ∙

∙ 05/12/2016

An Empirical-Bayes Score for Discrete Bayesian Networks

Bayesian network structure learning is often performed in a Bayesian set...

0 Marco Scutari, et al. ∙

∙ 06/30/2014

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

It is well known in the literature that the problem of learning the stru...

0 Marco Scutari, et al. ∙

∙ 10/14/2012

Graphical Modelling in Genetics and Systems Biology

Graphical modelling has a long history in statistics as a tool for the a...

0 Marco Scutari, et al. ∙

∙ 01/19/2012

On the Prior and Posterior Distributions Used in Graphical Modelling

Graphical model learning and inference are often performed using Bayesia...

0 Marco Scutari, et al. ∙

∙ 04/05/2011

On Identifying Significant Edges in Graphical Models of Molecular Networks

Objective: Modelling the associations from high-throughput experimental ...

0 Marco Scutari, et al. ∙

∙ 01/27/2011

Bayesian Network Structure Learning with Permutation Tests

In literature there are several studies on the performance of Bayesian n...

0 Marco Scutari, et al. ∙

∙ 09/09/2009

Structure Variability in Bayesian Networks

The structure of a Bayesian network encodes most of the information abou...

0 Marco Scutari, et al. ∙

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