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07/30/2023
Using Staged Tree Models for Health Data: Investigating Invasive Fungal Infections by Aspergillus and Other Filamentous Fungi
Machine learning models are increasingly used in the medical domain to s...
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05/21/2023
Discovering Causal Relations and Equations from Data
Physics is a field of science that has traditionally used the scientific...
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01/02/2023
Learning and interpreting asymmetry-labeled DAGs: a case study on COVID-19 fear
Bayesian networks are widely used to learn and reason about the dependen...
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06/14/2022
Highly Efficient Structural Learning of Sparse Staged Trees
Several structural learning algorithms for staged tree models, an asymme...
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03/08/2022
Structural Learning of Simple Staged Trees
Bayesian networks faithfully represent the symmetric conditional indepen...
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08/04/2021
Staged trees and asymmetry-labeled DAGs
Bayesian networks are a widely-used class of probabilistic graphical mod...
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06/08/2021
Context-Specific Causal Discovery for Categorical Data Using Staged Trees
Causal discovery algorithms aims at untangling complex causal relationsh...
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12/26/2020
A new class of generative classifiers based on staged tree models
Generative models for classification use the joint probability distribut...
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06/04/2020
Learning DAGs without imposing acyclicity
We explore if it is possible to learn a directed acyclic graph (DAG) fro...
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06/02/2020
Sparse Cholesky covariance parametrization for recovering latent structure in ordered data
The sparse Cholesky parametrization of the inverse covariance matrix can...
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05/21/2020
Graphical continuous Lyapunov models
The linear Lyapunov equation of a covariance matrix parametrizes the equ...
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04/14/2020
The R Package stagedtrees for Structural Learning of Stratified Staged Trees
stagedtrees is an R package which includes several algorithms for learni...
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02/21/2020
Causal structure learning from time series: Large regression coefficients may predict causal links better in practice than small p-values
In this article, we describe the algorithms for causal structure learnin...
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09/03/2019
Generating random Gaussian graphical models
Structure learning methods for covariance and concentration graphs are o...
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11/12/2018
Markov Property in Generative Classifiers
We show that, for generative classifiers, conditional independence corre...
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09/02/2018
A fast Metropolis-Hastings method for generating random correlation matrices
We propose a novel Metropolis-Hastings algorithm to sample uniformly fro...
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07/09/2018