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Publications of Author

1. Sam Maes, Philippe Leray
   Multi-Agent Causal Models for Dependability Analysis. [Citation Graph (0, 0)][DBLP]
   ARES, 2006, pp:794-798 [Conf]
   
2. Stijn Meganck, Sam Maes, Bernard Manderick, Philippe Leray
   A Learning Algorithm for Multi-Agent Causal Models. [Citation Graph (0, 0)][DBLP]
   EUMAS, 2005, pp:190-201 [Conf]
   
3. Olivier François, Philippe Leray
   Apprentissage de structure des réseaux bayésiens et données incomplètes. [Citation Graph (0, 0)][DBLP]
   EGC, 2005, pp:127-132 [Conf]
   
4. Grégory Mallet, Philippe Leray, Hubert Polaert
   Méthodes statistiques et modèles thermiques compacts. [Citation Graph (0, 0)][DBLP]
   EGC, 2007, pp:213-214 [Conf]
   
5. Stijn Meganck, Sam Maes, Bernard Manderick, Philippe Leray
   Distributed learning of Multi-Agent Causal Models. [Citation Graph (0, 0)][DBLP]
   IAT, 2005, pp:285-288 [Conf]
   
6. Philippe Leray, Patrick Gallinari, Elisabeth Didelet
   Diagnosis Tools for Telecommunication Network Traffic Management. [Citation Graph (0, 0)][DBLP]
   ICANN, 1996, pp:209-214 [Conf]
   
7. Stijn Meganck, Philippe Leray, Bernard Manderick
   Learning Causal Bayesian Networks from Observations and Experiments: A Decision Theoretic Approach. [Citation Graph (0, 0)][DBLP]
   MDAI, 2006, pp:58-69 [Conf]
   
8. Iyad Zaarour, Laurent Heutte, Philippe Leray, Jacques Labiche, Bassam Eter, Daniel Mellier
   Clustering And Bayesian Network Approaches For Discovering Handwriting Strategies Of Primary School Children. [Citation Graph (0, 0)][DBLP]
   IJPRAI, 2004, v:18, n:7, pp:1233-1251 [Journal]
   
9. Stijn Meganck, Philippe Leray, Bernard Manderick
   Causal Graphical Models with Latent Variables: Learning and Inference. [Citation Graph (0, 0)][DBLP]
   ECSQARU, 2007, pp:5-16 [Conf]
   
10. 
    Reliability Analysis using Graphical Duration Models. [Citation Graph (, )][DBLP]
    
    
11. 
    Integrating Ontological Knowledge for Iterative Causal Discovery and Visualization. [Citation Graph (, )][DBLP]
    
    
12. 
    Probability Density Estimation by Perturbing and Combining Tree Structured Markov Networks. [Citation Graph (, )][DBLP]
    
    
13. 
    Generation of Incompliete Test-Data usinng Bayesinan Networks. [Citation Graph (, )][DBLP]
    
    
14. 
    Bayesian Network-Based Approaches for Severe Attack Prediction and Handling IDSs' Reliability. [Citation Graph (, )][DBLP]
    
    
15. 
    Learning Semi-Markovian Causal Models using Experiments. [Citation Graph (, )][DBLP]
    
    
16. 
    Learning the Tree Augmented Naive Bayes Classifier from incomplete datasets. [Citation Graph (, )][DBLP]
    
    
17. 
    Combining classifiers for harmful document filtering. [Citation Graph (, )][DBLP]