Stijn Meganck

发表

Learning Causal Graphical Models with latent variables

Philippe Leray, Sam Maes, Stijn Meganck, 2006 .

Distributed learning of multi-agent causal models

Bernard Manderick, Philippe Leray, Sam Maes, 2005, IEEE/WIC/ACM International Conference on Intelligent Agent Technology.

Learning Causal Bayesian Networks from Observations and Experiments: A Decision Theoretic Approach

Bernard Manderick, Philippe Leray, Stijn Meganck, 2006, MDAI.

An integral approach to causal inference with latent variables

Philippe Leray, Sam Maes, Stijn Meganck, 2007 .

Batch effect removal methods for microarray gene expression data integration: a survey

Hugues Bersini, Colin Molter, Ann Nowé, 2013, Briefings Bioinform..

Causal discovery in non-ideal frameworks. Information interaction intelligence

Bernard Manderick, Philippe Leray, Stijn Meganck, 2009 .

Identification in Chain Multi-Agent Causal Models

Bernard Manderick, Sam Maes, Stijn Meganck, 2005, FLAIRS Conference.

Learning Semi-Markovian Causal Models using Experiments

Bernard Manderick, Philippe Leray, Sam Maes, 2006, Probabilistic Graphical Models.

Conservative independence-based causal structure learning in absence of adjacency faithfulness

Jan Lemeire, Francesco Cartella, Tingting Liu, 2012, Int. J. Approx. Reason..

Comparison of Merging and Meta-Analysis as Alternative Approaches for Integrative Gene Expression Analysis

Ann Nowé, Stijn Meganck, Cosmin Lazar, 2014, ISRN bioinformatics.

Detecting Marginal and Conditional Independencies between Events and Learning Their Causal Structure

Albrecht Zimmermann, Jan Lemeire, Stijn Meganck, 2013, ECSQARU.

Unlocking the potential of publicly available microarray data using inSilicoDb and inSilicoMerging R/Bioconductor packages

Hugues Bersini, Colin Molter, Ann Nowé, 2012, BMC Bioinformatics.

Negotiation for Calculating Causal Effects in Bi-Agent Causal Models

Bernard Manderick, Sam Maes, Stijn Meganck, 2005 .

Identification of Causal Effects in Multi-Agent Causal Models

Bernard Manderick, Sam Maes, Stijn Meganck, 2005, Artificial Intelligence and Applications.

Inference in multi-agent causal models

Bernard Manderick, Sam Maes, Stijn Meganck, 2007, Int. J. Approx. Reason..

Causal Graphical Models with Latent Variables: Learning and Inference

Bernard Manderick, Philippe Leray, Sam Maes, 2008, Innovations in Bayesian Networks.

Sequential Application of Feature Selection and Extraction for Predicting Breast Cancer Aggressiveness

Hugues Bersini, Ann Nowé, Nic Walker, 2010, CSBio.

Causal inference in graphical models with latent variables. From theory to practice.

Philippe Leray, Sam Maes, Stijn Meganck, 2006 .

An improved segmentation-based HMM learning method for Condition-based Maintenance

Jan Lemeire, Tingting Liu, Francesco Cartella, 2012 .

A Learning Algorithm for Multi-Agent Causal Models

Bernard Manderick, Philippe Leray, Sam Maes, 2005, EUMAS.

inSilicoDb: an R/Bioconductor package for accessing human Affymetrix expert-curated datasets from GEO

Hugues Bersini, Colin Molter, Ann Nowé, 2011, Bioinform..

Causal Inference in Multi-Agent Causal Models

Bernard Manderick, Sam Maes, Stijn Meganck, 2005, BNAIC.

Towards an Integral Approach for Modeling Causality

Stijn Meganck, S. Meganck, 2008 .

Causal Graphical Models with Latent Variables: Learning and Inference

Bernard Manderick, Philippe Leray, Stijn Meganck, 2007, ECSQARU.

Inferring the causal decomposition under the presence of deterministic relations

Jan Lemeire, Francesco Cartella, Tingting Liu, 2011, ESANN.

GENESHIFT: A Nonparametric Approach for Integrating Microarray Gene Expression Data Based on the Inner Product as a Distance Measure between the Distributions of Genes

Hugues Bersini, Colin Molter, Ann Nowé, 2013, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Validation of Merging Techniques for Cancer Microarray Data Sets

Hugues Bersini, Ann Nowé, Stijn Meganck, 2009, Aust. J. Intell. Inf. Process. Syst..

Online adaptive learning of Left-Right Continuous HMM for bearings condition assessment

Hichem Sahli, Francesco Cartella, Tingting Liu, 2012 .

Explaining Subgroups through Ontologies

Nada Lavrac, Vid Podpecan, Anze Vavpetic, 2012, PRICAI.

Applying subgroup discovery for the analysis of string quartet movements

Bernard Manderick, Ann Nowé, Darrell Conklin, 2010, MML '10.

A Survey on Filter Techniques for Feature Selection in Gene Expression Microarray Analysis

Hugues Bersini, Colin Molter, Ann Nowé, 2012, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Descriptive Subgroup Mining of Folk Music

Bernard Manderick, Darrell Conklin, Ruben Hillewaere, 2009 .

InSilico DB genomic datasets hub: an efficient starting point for analyzing genome-wide studies in GenePattern, Integrative Genomics Viewer, and R/Bioconductor

Hugues Bersini, Colin Molter, Ann Nowé, 2012, Genome Biology.