Concha Bielza

ORCID

Publication Activity (10 Years)

Years Active: 1999-2023
Publications (10 Years): 89

Top Venues

CoRR

PGM

Int. J. Approx. Reason.

Int. J. Intell. Syst.

Publications

Carlos Villa-Blanco, Alessandro Bregoli, Concha Bielza, Pedro Larrañaga, Fabio Stella
Constraint-based and hybrid structure learning of multidimensional continuous-time Bayesian network classifiers. Int. J. Approx. Reason. 159 (2023)
Carlos Puerto-Santana, Concha Bielza, Pedro Larrañaga, Gustav Eje Henter
Context-specific kernel-based hidden Markov model for time series analysis. CoRR (2023)
Gabriel Valverde, David Quesada, Pedro Larrañaga, Concha Bielza
Causal reinforcement learning based on Bayesian networks applied to industrial settings. Eng. Appl. Artif. Intell. 125 (2023)
David Quesada, Pedro Larrañaga, Concha Bielza
Classifying the evolution of COVID-19 severity on patients with combined dynamic Bayesian networks and neural networks. CoRR (2023)
Dafne Lozano, Luis Bote, Concha Bielza, Pedro Larrañaga, María Sabater, Juan Ramón Gimeno, Sergio Muñoz, Francisco Javier Gimeno-Blanes, José Luis Rojo-Álvarez
High-Dimensional Feature Characterization of Single Nucleotide Variants in Hypertrophic Cardiomyopathy. CinC (2023)
Carlos Puerto-Santana, Pedro Larrañaga, Concha Bielza
Feature subset selection in data-stream environments using asymmetric hidden Markov models and novelty detection. Neurocomputing 554 (2023)
Jorge Casajús-Setién, Concha Bielza, Pedro Larrañaga
Anomaly-Based Intrusion Detection in IIoT Networks Using Transformer Models. CSR (2023)
José Luis Moreno-Rodríguez, Pedro Larrañaga, Concha Bielza
NeuroSuites: An online platform for running neuroscience, statistical, and machine learning tools. Frontiers Neuroinformatics 17 (2023)
Vicente P. Soloviev, Concha Bielza, Pedro Larrañaga
Quantum approximate optimization algorithm for Bayesian network structure learning. Quantum Inf. Process. 22 (1) (2023)
Vicente P. Soloviev, Pedro Larrañaga, Concha Bielza
Variational Quantum Algorithm Parameter Tuning with Estimation of Distribution Algorithms. CEC (2023)
Enrique Valero-Leal, Concha Bielza, Pedro Larrañaga, Silja Renooij
Efficient search for relevance explanations using MAP-independence in Bayesian networks. Int. J. Approx. Reason. 160 (2023)
David Atienza, Concha Bielza, Pedro Larrañaga
Semiparametric Bayesian networks. Inf. Sci. 584 (2022)
Fernando Rodriguez-Sanchez, Concha Bielza, Pedro Larrañaga
Multipartition clustering of mixed data with Bayesian networks. Int. J. Intell. Syst. 37 (3) (2022)
Vicente P. Soloviev, Pedro Larrañaga, Concha Bielza
Quantum parametric circuit optimization with estimation of distribution algorithms. GECCO Companion (2022)
David Atienza, Concha Bielza, Pedro Larrañaga
PyBNesian: An extensible python package for Bayesian networks. Neurocomputing 504 (2022)
Vicente P. Soloviev, Pedro Larrañaga, Concha Bielza
Estimation of distribution algorithms using Gaussian Bayesian networks to solve industrial optimization problems constrained by environment variables. J. Comb. Optim. 44 (2) (2022)
David Quesada, Concha Bielza, Pedro Fontán, Pedro Larrañaga
Piecewise forecasting of nonlinear time series with model tree dynamic Bayesian networks. Int. J. Intell. Syst. 37 (11) (2022)
Carlos Villa-Blanco, Alessandro Bregoli, Concha Bielza, Pedro Larrañaga, Fabio Stella
Structure learning algorithms for multidimensional continuous-time Bayesian network classifiers. PGM (2022)
Carlos Puerto-Santana, Pedro Larrañaga, Concha Bielza
Autoregressive Asymmetric Linear Gaussian Hidden Markov Models. IEEE Trans. Pattern Anal. Mach. Intell. 44 (9) (2022)
Enrique Valero-Leal, Pedro Larrañaga, Concha Bielza
Interpreting Time-Varying Dynamic Bayesian Networks for Earth Climate Modelling. PGM (2022)
Vicente P. Soloviev, Concha Bielza, Pedro Larrañaga
Quantum Approximate Optimization Algorithm for Bayesian network structure learning. CoRR (2022)
Carlos Puerto-Santana, Concha Bielza, Javier Diaz-Rozo, Guillem Ramirez-Gargallo, Filippo Mantovani, Gaizka Virumbrales, Jesús Labarta, Pedro Larrañaga
Asymmetric HMMs for Online Ball-Bearing Health Assessments. IEEE Internet Things J. 9 (20) (2022)
Jorge Casajús-Setién, Concha Bielza, Pedro Larrañaga
Evolutive Adversarially-Trained Bayesian Network Autoencoder for Interpretable Anomaly Detection. PGM (2022)
David Quesada, Gabriel Valverde, Pedro Larrañaga, Concha Bielza
Long-term forecasting of multivariate time series in industrial furnaces with dynamic Gaussian Bayesian networks. Eng. Appl. Artif. Intell. 103 (2021)
Carlos Puerto-Santana, Pedro Larrañaga, Javier Diaz-Rozo, Concha Bielza
An Online Feature Selection Methodology for Ball-Bearing Harmonic Frequencies Based on HMMs. SOCO (2021)
Bojan Mihaljevic, Concha Bielza, Pedro Larrañaga
Bayesian networks for interpretable machine learning and optimization. Neurocomputing 456 (2021)
Mario Michiels, Pedro Larrañaga, Concha Bielza
BayeSuites: An open web framework for massive Bayesian networks focused on neuroscience. Neurocomputing 428 (2021)
Bojan Mihaljevic, Pedro Larrañaga, Concha Bielza
Comparing the Electrophysiology and Morphology of Human and Mouse Layer 2/3 Pyramidal Neurons With Bayesian Networks. Frontiers Neuroinformatics 15 (2021)
Carlos Villa-Blanco, Pedro Larrañaga, Concha Bielza
Multidimensional continuous time Bayesian network classifiers. Int. J. Intell. Syst. 36 (12) (2021)
David Atienza, Concha Bielza, Pedro Larrañaga
Semiparametric Bayesian Networks. CoRR (2021)
Santiago Gil-Begue, Concha Bielza, Pedro Larrañaga
Multi-dimensional Bayesian network classifiers: A survey. Artif. Intell. Rev. 54 (1) (2021)
David Quesada, Concha Bielza, Pedro Larrañaga
Structure Learning of High-Order Dynamic Bayesian Networks via Particle Swarm Optimization with Order Invariant Encoding. HAIS (2021)
Vicente P. Soloviev, Concha Bielza, Pedro Larrañaga
Quantum-Inspired Estimation Of Distribution Algorithm To Solve The Travelling Salesman Problem. CEC (2021)
Carlos Puerto-Santana, Pedro Larrañaga, Concha Bielza
Autoregressive Asymmetric Linear Gaussian Hidden Markov Models. CoRR (2020)
Irene Córdoba, Concha Bielza, Pedro Larrañaga, Gherardo Varando
Sparse Cholesky covariance parametrization for recovering latent structure in ordered data. CoRR (2020)
Irene Córdoba, Gherardo Varando, Concha Bielza, Pedro Larrañaga
On generating random Gaussian graphical models. Int. J. Approx. Reason. 125 (2020)
Nikolas Bernaola, Mario Michiels, Concha Bielza, Pedro Larrañaga
BayesSuites: An Open Web Framework for Visualization of Massive Bayesian Networks. PGM (2020)
Irene Córdoba, Concha Bielza, Pedro Larrañaga, Gherardo Varando
Sparse Cholesky Covariance Parametrization for Recovering Latent Structure in Ordered Data. IEEE Access 8 (2020)
Fernando Rodriguez-Sanchez, Pedro Larrañaga, Concha Bielza
Incremental Learning of Latent Forests. IEEE Access 8 (2020)
Javier Diaz-Rozo, Concha Bielza, Pedro Larrañaga
Machine-tool condition monitoring with Gaussian mixture models-based dynamic probabilistic clustering. Eng. Appl. Artif. Intell. 89 (2020)
Ignacio Leguey, Pedro Larrañaga, Concha Bielza, Shogo Kato
A circular-linear dependence measure under Johnson-Wehrly distributions and its application in Bayesian networks. Inf. Sci. 486 (2019)
Sergio Luengo-Sanchez, Pedro Larrañaga, Concha Bielza
A Directional-Linear Bayesian Network and Its Application for Clustering and Simulation of Neural Somas. IEEE Access 7 (2019)
Marco Benjumeda, Sergio Luengo-Sanchez, Pedro Larrañaga, Concha Bielza
Tractable learning of Bayesian networks from partially observed data. Pattern Recognit. 91 (2019)
Marco Benjumeda, Concha Bielza, Pedro Larrañaga
Learning tractable Bayesian networks in the space of elimination orders. Artif. Intell. 274 (2019)
Ignacio Leguey, Concha Bielza, Pedro Larrañaga
Circular Bayesian classifiers using wrapped Cauchy distributions. Data Knowl. Eng. 122 (2019)
Carlos Puerto-Santana, Concha Bielza, Pedro Larrañaga
Asymmetric Hidden Markov Models with Continuous Variables. CAEPIA (2018)
Santiago Gil-Begue, Pedro Larrañaga, Concha Bielza
Multi-dimensional Bayesian Network Classifier Trees. IDEAL (1) (2018)
Sergio Luengo-Sanchez, Isabel Fernaud, Concha Bielza, Ruth Benavides-Piccione, Pedro Larrañaga, Javier DeFelipe
3D morphology-based clustering and simulation of human pyramidal cell dendritic spines. PLoS Comput. Biol. 14 (6) (2018)
Laura Anton-Sanchez, Felix Effenberger, Concha Bielza, Pedro Larrañaga, Hermann Cuntz
A regularity index for dendrites - local statistics of a neuron's input space. PLoS Comput. Biol. 14 (11) (2018)
Fernando Rodriguez-Sanchez, Pedro Larrañaga, Concha Bielza
Discrete model-based clustering with overlapping subsets of attributes. PGM (2018)
Irene Córdoba, Concha Bielza, Pedro Larrañaga
Towards Gaussian Bayesian Network Fusion. CoRR (2018)
Bojan Mihaljevic, Pedro Larrañaga, Ruth Benavides-Piccione, Sean Hill, Javier DeFelipe, Concha Bielza
Towards a supervised classification of neocortical interneuron morphologies. BMC Bioinform. 19 (1) (2018)
Irene Córdoba, Gherardo Varando, Concha Bielza, Pedro Larrañaga
A partial orthogonalization method for simulating covariance and concentration graph matrices. PGM (2018)
Irene Córdoba-Sánchez, Eduardo C. Garrido-Merchán, Daniel Hernández-Lobato, Concha Bielza, Pedro Larrañaga
Bayesian optimization of the PC algorithm for learning Gaussian Bayesian networks. CoRR (2018)
Bojan Mihaljevic, Concha Bielza, Pedro Larrañaga
bnclassify: Learning Bayesian Network Classifiers. R J. 10 (2) (2018)
Marco Benjumeda, Concha Bielza, Pedro Larrañaga
Tractability of most probable explanations in multidimensional Bayesian network classifiers. Int. J. Approx. Reason. 93 (2018)
Irene Córdoba, Eduardo C. Garrido-Merchán, Daniel Hernández-Lobato, Concha Bielza, Pedro Larrañaga
Bayesian Optimization of the PC Algorithm for Learning Gaussian Bayesian Networks. CAEPIA (2018)
Gherardo Varando, Concha Bielza, Pedro Larrañaga, Eva Riccomagno
Markov Property in Generative Classifiers. CoRR (2018)
Bojan Mihaljevic, Concha Bielza, Pedro Larrañaga
Learning Bayesian network classifiers with completed partially directed acyclic graphs. PGM (2018)
Irene Córdoba, Gherardo Varando, Concha Bielza, Pedro Larrañaga
A Fast Metropolis-Hastings Method for Generating Random Correlation Matrices. IDEAL (1) (2018)
Javier Diaz-Rozo, Concha Bielza, Pedro Larrañaga
Clustering of Data Streams With Dynamic Gaussian Mixture Models: An IoT Application in Industrial Processes. IEEE Internet Things J. 5 (5) (2018)
Luis Rodriguez-Lujan, Pedro Larrañaga, Concha Bielza
Frobenius Norm Regularization for the Multivariate Von Mises Distribution. Int. J. Intell. Syst. 32 (2) (2017)
Laura Anton-Sanchez, Concha Bielza, Pedro Larrañaga
Network design through forests with degree- and role-constrained minimum spanning trees. J. Heuristics 23 (1) (2017)
Pablo Fernandez-Gonzalez, Concha Bielza, Pedro Larrañaga
Univariate and bivariate truncated von Mises distributions. Prog. Artif. Intell. 6 (2) (2017)
Javier Mesonero, Concha Bielza, Pedro Larrañaga
Architecture for anomaly detection in a laser heating surface process. ETFA (2017)
Hanen Borchani, Pedro Larrañaga, João Gama, Concha Bielza
Mining multi-dimensional concept-drifting data streams using Bayesian network classifiers. Intell. Data Anal. 20 (2) (2016)
Marco Benjumeda, Concha Bielza, Pedro Larrañaga
Learning Tractable Multidimensional Bayesian Network Classifiers. Probabilistic Graphical Models (2016)
Irene Córdoba-Sánchez, Concha Bielza, Pedro Larrañaga
A review of undirected and acyclic directed Gaussian Markov model selection and estimation. CoRR (2016)
Gherardo Varando, Concha Bielza, Pedro Larrañaga
Decision functions for chain classifiers based on Bayesian networks for multi-label classification. Int. J. Approx. Reason. 68 (2016)
Ignacio Leguey, Concha Bielza, Pedro Larrañaga
Tree-Structured Bayesian Networks for Wrapped Cauchy Directional Distributions. CAEPIA (2016)
Sergio Luengo-Sanchez, Concha Bielza, Pedro Larrañaga
Hybrid Gaussian and von Mises Model-Based Clustering. ECAI (2016)
Laura Anton-Sanchez, Concha Bielza, Ruth Benavides-Piccione, Javier DeFelipe, Pedro Larrañaga
Dendritic and Axonal Wiring Optimization of Cortical GABAergic Interneurons. Neuroinformatics 14 (4) (2016)
Marco Benjumeda, Pedro Larrañaga, Concha Bielza
Learning Bayesian networks with low inference complexity. Prog. Artif. Intell. 5 (1) (2016)
David Atienza, Concha Bielza, Javier Díaz, Pedro Larrañaga
Anomaly Detection with a Spatio-Temporal Tracking of the Laser Spot. STAIRS (2016)
Alfonso Ibáñez, Rubén Armañanzas, Concha Bielza, Pedro Larrañaga
Genetic algorithms and Gaussian Bayesian networks to uncover the predictive core set of bibliometric indices. J. Assoc. Inf. Sci. Technol. 67 (7) (2016)
Alberto Ogbechie, Javier Diaz-Rozo, Pedro Larrañaga, Concha Bielza
Dynamic Bayesian Network-Based Anomaly Detection for In-Process Visual Inspection of Laser Surface Heat Treatment. ML4CPS (2016)
Hossein Karshenas, Concha Bielza, Pedro Larrañaga
Interval-based ranking in noisy evolutionary multi-objective optimization. Comput. Optim. Appl. 61 (2) (2015)
Bojan Mihaljevic, Ruth Benavides-Piccione, Luis Guerra, Javier DeFelipe, Pedro Larrañaga, Concha Bielza
Classifying GABAergic interneurons with semi-supervised projected model-based clustering. Artif. Intell. Medicine 65 (1) (2015)
Irene Córdoba-Sánchez, Concha Bielza, Pedro Larrañaga
Towards Gaussian Bayesian Network Fusion. ECSQARU (2015)
Concha Bielza, João Gama, Alípio Jorge, Indre Zliobaite
Guest Editors introduction: special issue of the ECMLPKDD 2015 journal track. Mach. Learn. 100 (2-3) (2015)
Concha Bielza, João Gama, Alípio Jorge, Indre Zliobaite
Guest editors introduction: special issue of the ECMLPKDD 2015 journal track. Data Min. Knowl. Discov. 29 (5) (2015)
Pedro L. López-Cruz, Concha Bielza, Pedro Larrañaga
Directional naive Bayes classifiers. Pattern Anal. Appl. 18 (2) (2015)
Bojan Mihaljevic, Ruth Benavides-Piccione, Concha Bielza, Javier DeFelipe, Pedro Larrañaga
Bayesian Network Classifiers for Categorizing Cortical GABAergic Interneurons. Neuroinformatics 13 (2) (2015)
Gherardo Varando, Concha Bielza, Pedro Larrañaga
Decision boundary for discrete Bayesian network classifiers. J. Mach. Learn. Res. 16 (2015)
Javier Díaz, Concha Bielza, Jose L. Ocaña, Pedro Larrañaga
Development of a Cyber-Physical System based on selective Gaussian naïve Bayes model for a self-predict laser surface heat treatment process control. ML4CPS (2015)
Luis Rodriguez-Lujan, Concha Bielza, Pedro Larrañaga
Regularized Multivariate von Mises Distribution. CAEPIA (2015)
Concha Bielza, Serafín Moral, Antonio Salmerón
Recent Advances in Probabilistic Graphical Models. Int. J. Intell. Syst. 30 (3) (2015)
Gherardo Varando, Pedro L. López-Cruz, Thomas D. Nielsen, Pedro Larrañaga, Concha Bielza
Conditional Density Approximations with Mixtures of Polynomials. Int. J. Intell. Syst. 30 (3) (2015)
Hanen Borchani, Gherardo Varando, Concha Bielza, Pedro Larrañaga
A survey on multi-output regression. WIREs Data Mining Knowl. Discov. 5 (5) (2015)
Pedro L. López-Cruz, Pedro Larrañaga, Javier DeFelipe, Concha Bielza
Bayesian network modeling of the consensus between experts: An application to neuron classification. Int. J. Approx. Reason. 55 (1) (2014)
Jesse Read, Concha Bielza, Pedro Larrañaga
Multi-Dimensional Classification with Super-Classes. IEEE Trans. Knowl. Data Eng. 26 (7) (2014)
Bojan Mihaljevic, Concha Bielza, Ruth Benavides-Piccione, Javier DeFelipe, Pedro Larrañaga
Multi-dimensional classification of GABAergic interneurons with Bayesian network-modeled label uncertainty. Frontiers Comput. Neurosci. 8 (2014)
Pedro L. López-Cruz, Concha Bielza, Pedro Larrañaga
Learning mixtures of polynomials of multidimensional probability densities from data using B-spline interpolation. Int. J. Approx. Reason. 55 (4) (2014)
Luis Guerra, Concha Bielza, Víctor Robles, Pedro Larrañaga
Semi-supervised projected model-based clustering. Data Min. Knowl. Discov. 28 (4) (2014)
Luis Enrique Sucar, Concha Bielza, Eduardo F. Morales, Pablo Hernandez-Leal, Julio H. Zaragoza, Pedro Larrañaga
Multi-label classification with Bayesian network-based chain classifiers. Pattern Recognit. Lett. 41 (2014)
Hossein Karshenas, Roberto Santana, Concha Bielza, Pedro Larrañaga
Multiobjective Estimation of Distribution Algorithm Based on Joint Modeling of Objectives and Variables. IEEE Trans. Evol. Comput. 18 (4) (2014)
Concha Bielza, Pedro Larrañaga
Bayesian networks in neuroscience: a survey. Frontiers Comput. Neurosci. 8 (2014)
Concha Bielza, Pedro Larrañaga
Discrete Bayesian Network Classifiers: A Survey. ACM Comput. Surv. 47 (1) (2014)
Alfonso Ibáñez, Concha Bielza, Pedro Larrañaga
Cost-sensitive selective naive Bayes classifiers for predicting the increase of the h-index for scientific journals. Neurocomputing 135 (2014)
Gherardo Varando, Concha Bielza, Pedro Larrañaga
Expressive Power of Binary Relevance and Chain Classifiers Based on Bayesian Networks for Multi-label Classification. Probabilistic Graphical Models (2014)

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Publication Activity (10 Years)

Top Topics

Top Venues

Concha Bielza