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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...
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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...
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05/17/2023
Causal Discovery with Missing Data in a Multicentric Clinical Study
Causal inference for testing clinical hypotheses from observational data...
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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...
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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 ...
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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 ...
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05/12/2022
Comments on: "Hybrid Semiparametric Bayesian Networks"
Invited discussion on the paper "Hybrid Semiparametric Bayesian Networks...
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05/18/2021
Achieving Fairness with a Simple Ridge Penalty
Estimating a fair linear regression model subject to a user-defined leve...
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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...
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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...
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07/07/2020
Constraint-Based Learning for Continuous-Time Bayesian Networks
Dynamic Bayesian networks have been well explored in the literature as d...
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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...
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06/15/2019
From Incomplete, Dynamic Data to Bayesian Networks
Bayesian networks are a versatile and powerful tool to model complex phe...
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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...
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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...
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08/02/2017
Dirichlet Bayesian Network Scores and the Maximum Entropy Principle
A classic approach for learning Bayesian networks from data is to select...
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04/12/2017
Beyond Uniform Priors in Bayesian Network Structure Learning
Bayesian network structure learning is often performed in a Bayesian set...
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05/12/2016
An Empirical-Bayes Score for Discrete Bayesian Networks
Bayesian network structure learning is often performed in a Bayesian set...
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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...
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10/14/2012
Graphical Modelling in Genetics and Systems Biology
Graphical modelling has a long history in statistics as a tool for the a...
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01/19/2012
On the Prior and Posterior Distributions Used in Graphical Modelling
Graphical model learning and inference are often performed using Bayesia...
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04/05/2011
On Identifying Significant Edges in Graphical Models of Molecular Networks
Objective: Modelling the associations from high-throughput experimental ...
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01/27/2011
Bayesian Network Structure Learning with Permutation Tests
In literature there are several studies on the performance of Bayesian n...
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09/09/2009
