research
∙
09/21/2023
On the Probability of Immunity
This work is devoted to the study of the probability of immunity, i.e. t...
share
research
∙
06/02/2023
Alternative Measures of Direct and Indirect Effects
There are a number of measures of direct and indirect effects in the lit...
research
∙
03/08/2023
Bounding the Probabilities of Benefit and Harm Through Sensitivity Parameters and Proxies
We present two methods for bounding the probabilities of benefit and har...
research
∙
09/15/2022
ρ-GNF : A Novel Sensitivity Analysis Approach Under Unobserved Confounders
We propose a new sensitivity analysis model that combines copulas and no...
research
∙
02/17/2022
Counterfactual Analysis of the Impact of the IMF Program on Child Poverty in the Global-South Region using Causal-Graphical Normalizing Flows
This work demonstrates the application of a particular branch of causal ...
research
∙
02/07/2022
Personalized Public Policy Analysis in Social Sciences using Causal-Graphical Normalizing Flows
Structural Equation/Causal Models (SEMs/SCMs) are widely used in epidemi...
research
∙
04/27/2021
Simple yet Sharp Sensitivity Analysis for Unmeasured Confounding
We present a method for assessing the sensitivity of the true causal eff...
research
∙
01/20/2021
On the Non-Monotonicity of a Non-Differentially Mismeasured Binary Confounder
Suppose that we are interested in the average causal effect of a binary ...
research
∙
12/21/2020
Towards Conditional Path Analysis
We extend path analysis by giving sufficient conditions for computing th...
research
∙
05/27/2020
On the Monotonicity of a Nondifferentially Mismeasured Binary Confounder
Suppose that we are interested in the average causal effect of a binary ...
research
∙
02/12/2020
Conditional Path Analysis in Singly-Connected Path Diagrams
We extend the classical path analysis by showing that, for a singly-conn...
research
∙
11/11/2018
Unifying Gaussian LWF and AMP Chain Graphs to Model Interference
An intervention may have an effect on units other than those to which th...
research
∙
06/21/2018
Identifiability of Gaussian Structural Equation Models with Dependent Errors Having Equal Variances
In this paper, we prove that some Gaussian structural equation models wi...
research
∙
11/23/2017
Identification of Strong Edges in AMP Chain Graphs
The essential graph is a distinguished member of a Markov equivalence cl...
research
∙
08/29/2017
Unifying DAGs and UGs
We introduce a new class of graphical models that generalizes Lauritzen-...
research
∙
12/22/2016
Causal Effect Identification in Acyclic Directed Mixed Graphs and Gated Models
We introduce a new family of graphical models that consists of graphs wi...
research
∙
12/04/2016
Representing Independence Models with Elementary Triplets
In an independence model, the triplets that represent conditional indepe...
research
∙
11/18/2015
Alternative Markov and Causal Properties for Acyclic Directed Mixed Graphs
We extend Andersson-Madigan-Perlman chain graphs by (i) relaxing the sem...
research
∙
01/27/2015
Factorization, Inference and Parameter Learning in Discrete AMP Chain Graphs
We address some computational issues that may hinder the use of AMP chai...
research
∙
12/10/2013
Every LWF and AMP chain graph originates from a set of causal models
This paper aims at justifying LWF and AMP chain graphs by showing that t...
research
∙
06/28/2013
Error AMP Chain Graphs
Any regular Gaussian probability distribution that can be represented by...
research
∙
05/03/2013
Marginal AMP Chain Graphs
We present a new family of models that is based on graphs that may have ...
research
∙
03/04/2013
Learning AMP Chain Graphs and some Marginal Models Thereof under Faithfulness: Extended Version
This paper deals with chain graphs under the Andersson-Madigan-Perlman (...
research
∙
01/30/2013
Approximate Counting of Graphical Models Via MCMC Revisited
In Peña (2007), MCMC sampling is applied to approximately calculate the ...
research
∙
01/16/2013
Combinatorial Optimization by Learning and Simulation of Bayesian Networks
This paper shows how the Bayesian network paradigm can be used in order ...
research
∙
10/19/2012
On Local Optima in Learning Bayesian Networks
This paper proposes and evaluates the k-greedy equivalence search algori...
research
∙
06/27/2012
Identifying the Relevant Nodes Without Learning the Model
We propose a method to identify all the nodes that are relevant to compu...
research
∙
06/20/2012
Reading Dependencies from Polytree-Like Bayesian Networks
We present a graphical criterion for reading dependencies from the minim...
research
∙
04/24/2012
Learning AMP Chain Graphs under Faithfulness
This paper deals with chain graphs under the alternative Andersson-Madig...
research
∙
09/25/2011
Towards Optimal Learning of Chain Graphs
In this paper, we extend Meek's conjecture (Meek 1997) from directed and...
research
∙
01/10/2011
Finding Consensus Bayesian Network Structures
Suppose that multiple experts (or learning algorithms) provide us with a...
research
∙
10/21/2010
Reading Dependencies from Covariance Graphs
The covariance graph (aka bi-directed graph) of a probability distributi...
research
∙
08/13/2010
