S. Moral

Luis M. de Campos, Serafín Moral, Francisco Javier García Castellano, 2011, 2011 11th International Conference on Intelligent Systems Design and Applications.

The behavioral meaning of the median

Inés Couso, Luciano Sánchez, Serafín Moral, 2015, Inf. Sci..

Computation of Kullback–Leibler Divergence in Bayesian Networks

A. Cano, S. Moral, Manuel Gómez-Olmedo, 2021, Entropy.

Imprecise probabilities for representing ignorance about a parameter

Serafín Moral, S. Moral, 2012, Int. J. Approx. Reason..

Imprecise probability models for learning multinomial distributions from data. Applications to learning credal networks

Andrés R. Masegosa, Serafín Moral, S. Moral, 2014, Int. J. Approx. Reason..

Propagating uncertain information forward

Luis M. de Campos, Serafín Moral, S. Moral, 1992, Int. J. Intell. Syst..

Credal Nets with Probabilities Estimated with an Extreme Imprecise Dirichlet Model

Andrés Cano, Manuel Gómez-Olmedo, A. Cano, 2007 .

A Review of Propagation Algorithms for Imprecise Probabilities

Serafín Moral, Andrés Cano, A. Cano, 1999, ISIPTA.

Probability Intervals: a Tool for uncertain Reasoning

Luis M. de Campos, Juan F. Huete, Serafín Moral, 1994, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

Convex Sets Of Probabilities Propagation By Simulated Annealing

Andrés Cano, Jose E. Cano, S. Moral, 1994 .

Probabilistic graphical models in artificial intelligence

Pedro Larrañaga, Serafín Moral, P. Larrañaga, 2011, Appl. Soft Comput..

Methods to Determine the Branching Attribute in Bayesian Multinets Classifiers

Andrés R. Masegosa, Serafín Moral, Francisco Javier García Castellano, 2005, ECSQARU.

Handbook of Defeasible Reasoning and Uncertainty Management Systems

Jürg Kohlas, Serafín Moral, S. Moral, 2000 .

Increasing diversity in random forest learning algorithm via imprecise probabilities

Serafín Moral, Francisco Javier García Castellano, Joaquín Abellán, 2018, Expert Syst. Appl..

Flight Trajectory Clustering: a framework that uses Planned Route data

Carlos Morales, Serafin Moral, S. Moral, 2019, 2019 IEEE 14th International Symposium on Autonomous Decentralized System (ISADS).

A forward-backward Monte Carlo method for solving influence diagrams

Andrés Cano, Serafín Moral, Manuel Gómez-Olmedo, 2006, Int. J. Approx. Reason..

A Logical View of Probability

Nic Wilson, Serafín Moral, S. Moral, 1994, ECAI.

Removing partial inconsistency in valuation‐based systems

Serafín Moral, S. Moral, L. de Campos, 1997 .

Removing partial inconsistency in valuation-based systems

S. Moral, L. M. D. Campos, 1997, Int. J. Intell. Syst..

New skeleton-based approaches for Bayesian structure learning of Bayesian networks

Andrés R. Masegosa, Serafín Moral, S. Moral, 2013, Appl. Soft Comput..

Heuristic Algorithms for the Triangulation of Graphs

Serafín Moral, Andrés Cano, A. Cano, 1994, IPMU.

Lazy evaluation in penniless propagation over join trees

Serafín Moral, Antonio Salmerón, Andrés Cano, 2002, Networks.

Locally averaged Bayesian Dirichlet metrics for learning the structure and the parameters of Bayesian networks

Andrés R. Masegosa, Serafín Moral, Andrés Cano, 2013, Int. J. Approx. Reason..

Inference in Bayesian Networks with Recursive Probability Trees: Data Structure Definition and Operations

Antonio Salmerón, Andrés Cano, Cora B. Pérez-Ariza, 2013, Int. J. Intell. Syst..

Recursive Probability Trees for Bayesian Networks

Serafín Moral, Andrés Cano, Cora B. Pérez-Ariza, 2009, CAEPIA.

Estimating Conditional Probabilities by Mixtures of Low Order Conditional Distributions

Andrés Cano, Serafín Moral, Manuel Gómez-Olmedo, 2017, SUM.

A Bayesian approach to abrupt concept drift

Andrés Cano, Serafín Moral, Manuel Gómez-Olmedo, 2019, Knowl. Based Syst..

Revision rules for convex sets of probabilities

Nic Wilson, Serafín Moral, S. Moral, 1995 .

Binary Probability Trees for Bayesian Networks Inference

Serafín Moral, Andrés Cano, Manuel Gómez-Olmedo, 2009, ECSQARU.

Approximate Factorisation of Probability Trees

Serafín Moral, Irene Martínez, Carmelo Rodríguez, 2005, ECSQARU.

Partial abductive inference in Bayesian belief networks - an evolutionary computation approach by using problem-specific genetic operators

José A. Gámez, Luis M. de Campos, Serafín Moral, 2002, IEEE Trans. Evol. Comput..

Importance Sampling in Bayesian Networks Using Antithetic Variables

Serafín Moral, Antonio Salmerón, A. Salmerón, 2001, ECSQARU.

Mixing exact and importance sampling propagation algorithms in dependence graphs

Serafín Moral, Luis D. Hernández, S. Moral, 1997, Int. J. Intell. Syst..

Approximate inference in Bayesian networks using binary probability trees

Serafín Moral, Andrés Cano, Manuel Gómez-Olmedo, 2011, Int. J. Approx. Reason..

Partial Abductive Inference in Bayesian Networks By Using Probability Trees

José A. Gámez, Luis M. de Campos, Serafín Moral, 2003, ICEIS.

Partial Abductive Inference in Bayesian Networks: An Empirical Comparison Between GAs and EDAs

Luis M. de Campos, Pedro Larrañaga, Serafín Moral, 2002, Estimation of Distribution Algorithms.

Factorisation of Probability Trees and its Application to Inference in Bayesian Networks

Serafín Moral, Irene Martínez, Carmelo Rodríguez, 2002, Probabilistic Graphical Models.

A Monte Carlo algorithm for probabilistic propagation in belief networks based on importance sampling and stratified simulation techniques

Serafín Moral, Antonio Salmerón, Luis D. Hernández, 1998, Int. J. Approx. Reason..

A Bayesian stochastic search method for discovering Markov boundaries

Andrés R. Masegosa, Serafín Moral, S. Moral, 2012, Knowl. Based Syst..

Partial abductive inference in Bayesian belief networks using a genetic algorithm

José A. Gámez, Luis M. de Campos, Serafín Moral, 1999, Pattern Recognit. Lett..

An interactive approach for Bayesian network learning using domain/expert knowledge

S. Moral, A. Masegosa, 2013, Int. J. Approx. Reason..

An Importance Sampling Approach to Integrate Expert Knowledge When Learning Bayesian Networks From Data

Andrés R. Masegosa, Serafín Moral, Andrés Cano, 2010, IPMU.

Learning Bayesian network by a mesh of points

Serafín Moral, Luís Moreira, Byron Oviedo, 2015, 2016 IEEE Congress on Evolutionary Computation (CEC).

Building classification trees using the total uncertainty criterion

Serafín Moral, Joaquín Abellán, S. Moral, 2003, Int. J. Intell. Syst..

A Non-Specificity Measure for Convex Sets of Probability Distributions

Serafín Moral, Joaquín Abellán, S. Moral, 2000, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

Virtual Subconcept Drift Detection in Discrete Data Using Probabilistic Graphical Models

Andrés R. Masegosa, Rafael Cabañas, Andrés Cano, 2018, IPMU.

Partial abductive inference in Bayesian belief networks by simulated annealing

José A. Gámez, Luis M. de Campos, Serafín Moral, 2001, Int. J. Approx. Reason..

Accelerating chromosome evaluation for partial abductive inference in Bayesian networks by means of explanation set absorption

José A. Gámez, Luis M. de Campos, Serafín Moral, 2001, Int. J. Approx. Reason..

Symbolic and Quantitative Approaches to Reasoning and Uncertainty

Michael Clarke, Serafín Moral, Rudolf Kruse, 1991, Lecture Notes in Computer Science.

Disaggregated total uncertainty measure for credal sets

George J. Klir, Serafín Moral, Joaquín Abellán, 2006, Int. J. Gen. Syst..

Combining gene expression data and prior knowledge for inferring gene regulatory networks via Bayesian networks using structural restrictions

Serafín Moral, Andrés Cano, Luis M de Campos, 2019, Statistical applications in genetics and molecular biology.

Upper and lower fuzzy measures

Serafín Moral, Miguel Delgado, S. Moral, 1989 .

Hill-climbing and branch-and-bound algorithms for exact and approximate inference in credal networks

Serafín Moral, Joaquín Abellán, Andrés Cano, 2007, Int. J. Approx. Reason..

Discretization of Simulated Flight Parameters for Estimation of Situational Awareness Using Dynamic Bayesian Networks

Serafín Moral, Carlos Morales, S. Moral, 2015, 2015 IEEE Twelfth International Symposium on Autonomous Decentralized Systems.

Independence concepts in evidence theory

Inés Couso, Serafín Moral, S. Moral, 2010, Int. J. Approx. Reason..

Advances in Bayesian networks

José A. Gámez, Serafín Moral, Antonio Salmerón, 2004 .

Haplotype-based Classifiers to Predict Individual Susceptibility to Complex Diseases - An Example for Multiple Sclerosis

Andrés R. Masegosa, María M. Abad-Grau, Serafín Moral, 2012, BIOINFORMATICS.

Proceedings of the European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty

R. Kruse, S. Moral, Michael Clarke, 1991 .

Increasing Power by using Haplotype Similarity in a Multimarker Transmission/disequilibrium Test

Serafín Moral, María M. Abad-Grau, Rosana Montes-Soldado, 2013, J. Bioinform. Comput. Biol..

Value‐based potentials: Exploiting quantitative information regularity patterns in probabilistic graphical models

A. Cano, S. Moral, Manuel Gómez-Olmedo, 2021, Int. J. Intell. Syst..

Use of Explanation Treesto Describe the State Space of a Probabilistic-Based Abduction Problem

José A. Gámez, Serafín Moral, M. Julia Flores, 2008, Innovations in Bayesian Networks.

Using probability trees to compute marginals with imprecise probabilities

Serafín Moral, Andrés Cano, A. Cano, 2002, Int. J. Approx. Reason..

A semantics for possibility theory based on likelihoods

Didier Dubois, Henri Prade, Serafín Moral, 1995, Proceedings of 1995 IEEE International Conference on Fuzzy Systems..

Regression Methods Applied to Flight Variables for Situational Awareness Estimation Using Dynamic Bayesian Networks

Serafín Moral, Carlos Morales, S. Moral, 2016, Probabilistic Graphical Models.

Estimating mixtures of truncated exponentials in hybrid bayesian networks

Serafín Moral, Rafael Rumí, Antonio Salmerón, 2006 .

Mixtures of Truncated Exponentials in Hybrid Bayesian Networks

Serafín Moral, Rafael Rumí, Antonio Salmerón, 2001, ECSQARU.

Dynamic importance sampling in Bayesian networks based on probability trees

A. Salmerón, S. Moral, 2005, Int. J. Approx. Reason..

Dynamic Importance Sampling Computation in Bayesian Networks

Serafín Moral, Antonio Salmerón, A. Salmerón, 2003, ECSQARU.

Penniless propagation in join trees

Serafín Moral, Antonio Salmerón, Andrés Cano, 2000, Int. J. Intell. Syst..

Algorithms for Approximate Probability Propagation in Bayesian Networks

Serafín Moral, Antonio Salmerón, Andrés Cano, 2004 .

Extended Probability Trees for Probabilistic Graphical Models

Andrés Cano, Cora B. Pérez-Ariza, Serafín Moral, 2014, Probabilistic Graphical Models.

Learning recursive probability trees from probabilistic potentials

Antonio Salmerón, Andrés Cano, Cora B. Pérez-Ariza, 2012, Int. J. Approx. Reason..

Novel strategies to approximate probability trees in penniless propagation

Serafín Moral, Antonio Salmerón, Andrés Cano, 2003, Int. J. Intell. Syst..

Aggregation of Imprecise Probabilities

Serafín Moral, José del Sagrado, S. Moral, 1998 .

Propositional Information Systems

Jürg Kohlas, Serafín Moral, Rolf Haenni, 1999, J. Log. Comput..

Determining dependence relations using a new score based on imprecise probabilities

Serafín Moral, Joaquín Abellán, S. Moral, 2012, Intell. Data Anal..

Independence Concepts for Convex Sets of Probabilities

Luis M. de Campos, Serafín Moral, S. Moral, 1995, UAI.

Classification of fuzzy measures

Serafín Moral, María Teresa Lamata, M. T. Lamata, 1989 .

Calculating Uncertainty Intervals from Conditional Convex Sets of Probabilities

Serafín Moral, S. Moral, 1992, UAI.

Updating Uncertain Information

Luis M. de Campos, Serafín Moral, S. Moral, 1990, IPMU.

Application of a hill-climbing algorithm to exact and approximate inference in credal networks

Andrés Cano, Serafín Moral, Manuel Gómez-Olmedo, 2005, ISIPTA.

Sets of desirable gambles: Conditioning, representation, and precise probabilities

Inés Couso, Serafín Moral, S. Moral, 2011, Int. J. Approx. Reason..

Epistemic irrelevance on sets of desirable gambles

Serafín Moral, S. Moral, 2005, Annals of Mathematics and Artificial Intelligence.

Examples of Independence for Imprecise Probabilities

S. Moral, Inés Couso, Peter Walley, 1999, ISIPTA.

Imprecise Classification with Non-parametric Predictive Inference

Francisco Javier García Castellano, Joaquín Abellán, Carlos Javier Mantas, 2020, IPMU.

Maximum of Entropy for Credal Sets

Serafín Moral, Joaquín Abellán, S. Moral, 2003, Int. J. Uncertain. Fuzziness Knowl. Based Syst..