Diagnosis Tools for Telecommunication Network Traffic Management. - Philippe Leray 001; Patrick Gallinari; Elisabeth Didelet (ICANN, 1996)

De l'utilisation d'OBD pour la sélection de variables dans les perceptrons multicouches. - Philippe Leray 001; Patrick Gallinari (Rev. d'Intelligence Artif., 2001)

Combining classifiers for harmful document filtering. - Bruno Grilhères; Stephan Brunessaux; Philippe Leray 001 (RIAO, 2004)

Clustering And Bayesian Network Approaches For Discovering Handwriting Strategies Of Primary School Children. - Iyad Zaarour; Laurent Heutte; Philippe Leray 001; Jacques Labiche; Bassam Eter; Daniel Mellier (Int. J. Pattern Recognit. Artif. Intell., 2004)

Réseaux bayésiens pour la classification Méthodologie et illustration dans le cadre du diagnostic médical. - Philippe Leray 001; Olivier François (Rev. d'Intelligence Artif., 2004)

A Learning Algorithm for Multi-Agent Causal Models. - Stijn Meganck; Sam Maes; Bernard Manderick; Philippe Leray 001 (EUMAS, 2005)

Réseaux bayésiens pour le filtrage d'alarmes dans les systèmes de détection d'intrusions. - Ahmad Faour; Philippe Leray 001; Cédric Foll (EGC (Ateliers), 2005)

Apprentissage de structure des réseaux bayésiens et données incomplètes. - Olivier François; Philippe Leray 001 (EGC, 2005)

Distributed learning of Multi-Agent Causal Models. - Stijn Meganck; Sam Maes; Bernard Manderick; Philippe Leray 001 (IAT, 2005)

Réseaux bayésiens : Apprentissage et diagnostic de systemes complexes. - Philippe Leray 001 (2006)

Multi-Agent Causal Models for Dependability Analysis. - Sam Maes; Philippe Leray 001 (ARES, 2006)

Learning Causal Bayesian Networks from Observations and Experiments: A Decision Theoretic Approach. - Stijn Meganck; Philippe Leray 001; Bernard Manderick (MDAI, 2006)

Learning the Tree Augmented Naive Bayes Classifier from incomplete datasets. - Olivier François; Philippe Leray 001 (Probabilistic Graphical Models, 2006)

Learning Semi-Markovian Causal Models using Experiments. - Stijn Meganck; Sam Maes; Philippe Leray 001; Bernard Manderick (Probabilistic Graphical Models, 2006)

Causal Graphical Models with Latent Variables: Learning and Inference. - Stijn Meganck; Philippe Leray 001; Bernard Manderick (ECSQARU, 2007)

Méthodes statistiques et modèles thermiques compacts. - Grégory Mallet; Philippe Leray 001; Hubert Polaert (EGC, 2007)

Generation of Incompliete Test-Data usinng Bayesinan Networks. - Olivier François; Philippe Leray 001 (IJCNN, 2007)

Éditorial. - Philippe Leray 001 (Rev. d'Intelligence Artif., 2007)

Reliability Analysis using Graphical Duration Models. - Roland Donat; Laurent Bouillaut; Patrice Aknin; Philippe Leray 001 (ARES, 2008)

Causal Graphical Models with Latent Variables: Learning and Inference. - Philippe Leray 001; Stijn Meganck; Sam Maes; Bernard Manderick (Innovations in Bayesian Networks, 2008)

Probability Density Estimation by Perturbing and Combining Tree Structured Markov Networks. - Sourour Ammar; Philippe Leray 001; Boris Defourny; Louis Wehenkel (ECSQARU, 2009)

Integrating Ontological Knowledge for Iterative Causal Discovery and Visualization. - Montassar Ben Messaoud; Philippe Leray 001; Nahla Ben Amor (ECSQARU, 2009)

Learning Hierarchical Bayesian Networks for Genome-Wide Association Studies. - Raphaël Mourad; Christine Sinoquet; Philippe Leray 001 (COMPSTAT, 2010)

Towards sub-quadratic learning of probability density models in the form of mixtures of trees. - François Schnitzler; Philippe Leray 001; Louis Wehenkel (ESANN, 2010)

Bayesian Network-Based Approaches for Severe Attack Prediction and Handling IDSs' Reliability. - Karim Tabia; Philippe Leray 001 (IPMU (2), 2010)

Handling IDS' Reliability in Alert Correlation - A Bayesian Network-based Model for Handling IDS's Reliability and Controlling Prediction/False Alarm Rate Tradeoffs. - Karim Tabia; Philippe Leray 001 (SECRYPT, 2010)

A dynamic Bayesian network to represent discrete duration models. - Roland Donat; Philippe Leray 001; Laurent Bouillaut; Patrice Aknin (Neurocomputing, 2010)

Mixture of Markov Trees for Bayesian Network Structure Learning with Small Datasets in High Dimensional Space. - Sourour Ammar; Philippe Leray 001 (ECSQARU, 2011)

SemCaDo: A Serendipitous Strategy for Learning Causal Bayesian Networks Using Ontologies. - Montassar Ben Messaoud; Philippe Leray 001; Nahla Ben Amor (ECSQARU, 2011)

A Two-way Approach for Probabilistic Graphical Models Structure Learning and Ontology Enrichment. - Mouna Ben Ishak; Philippe Leray 001; Nahla Ben Amor (KEOD, 2011)

Discrete Exponential Bayesian Networks: An Extension of Bayesian Networks to Discrete Natural Exponential Families. - Aida Jarraya; Philippe Leray 001; Afif Masmoudi (ICTAI, 2011)

iMMPC: A Local Search Approach for Incremental Bayesian Network Structure Learning. - Amanullah Yasin; Philippe Leray 001 (IDA, 2011)

Multiple Hypothesis Testing and Quasi Essential Graph for Comparing Two Sets of Bayesian Networks. - Hoai-Tuong Nguyen; Philippe Leray 001; Gérard Ramstein (KES (2), 2011)

Efficiently Approximating Markov Tree Bagging for High-Dimensional Density Estimation. - François Schnitzler; Sourour Ammar; Philippe Leray 001; Pierre Geurts; Louis Wehenkel (ECML/PKDD (3), 2011)

A hierarchical Bayesian network approach for linkage disequilibrium modeling and data-dimensionality reduction prior to genome-wide association studies. - Raphaël Mourad; Christine Sinoquet; Philippe Leray 001 (BMC Bioinform., 2011)

Alert correlation: Severe attack prediction and controlling false alarm rate tradeoffs. - Karim Tabia; Philippe Leray 001 (Intell. Data Anal., 2011)

Forests of Latent Tree Models for the Detection of Genetic Associations. - Christine Sinoquet; Raphaël Mourad; Philippe Leray 001 (BIOINFORMATICS, 2012)

Forests of Latent Tree Models to Decipher Genotype-Phenotype Associations. - Christine Sinoquet; Raphaël Mourad; Philippe Leray 001 (BIOSTEC (Selected Papers), 2012)

iMMPC: Une approche locale pour l'apprentissage incrémental de la structure des réseaux bayésiens. - Amanullah Yasin; Philippe Leray 001 (EGC, 2012)

Discrete Exponential Bayesian Networks Structure Learning for Density Estimation. - Aida Jarraya; Philippe Leray 001; Afif Masmoudi (ICIC (3), 2012)

Probabilistic graphical models for genetic association studies. - Raphaël Mourad; Christine Sinoquet; Philippe Leray 001 (Briefings Bioinform., 2012)

Dynamic MMHC: A Local Search Algorithm for Dynamic Bayesian Network Structure Learning. - Ghada Trabelsi; Philippe Leray 001; Mounir Ben Ayed; Adel M. Alimi (IDA, 2013)

Active learning of causal Bayesian networks using ontologies: A case study. - Montassar Ben Messaoud; Philippe Leray 001; Nahla Ben Amor (IJCNN, 2013)

Imputation of Possibilistic Data for Structural Learning of Directed Acyclic Graphs. - Maroua Haddad 001; Nahla Ben Amor; Philippe Leray 001 (WILF, 2013)

Editorial: Uncertainty in Artificial Intelligence and Databases. - Salem Benferhat; Philippe Leray 001 (Int. J. Approx. Reason., 2013)

A Survey on Latent Tree Models and Applications. - Raphaël Mourad; Christine Sinoquet; Nevin Lianwen Zhang; Tengfei Liu; Philippe Leray 001 (J. Artif. Intell. Res., 2013)

Learning Probabilistic Relational Models Using Non-Negative Matrix Factorization. - Anthony Coutant; Philippe Leray 001; Hoel Le Capitaine (FLAIRS, 2014)

Probabilistic Cognitive Maps - Semantics of a Cognitive Map when the Values are Assumed to be Probabilities. - Aymeric Le Dorze; Béatrice Duval; Laurent Garcia; David Genest; Philippe Leray 001; Stéphane Loiseau (ICAART (1), 2014)

A Probabilistic Semantics for Cognitive Maps. - Aymeric Le Dorze; Béatrice Duval; Laurent Garcia; David Genest; Philippe Leray 001; Stéphane Loiseau (ICAART (Revised Selected Papers), 2014)

Advances in Learning with Bayesian Networks. - Philippe Leray 001 (ICAART (1), 2014)

Random Generation and Population of Probabilistic Relational Models and Databases. - Mouna Ben Ishak; Philippe Leray 001; Nahla Ben Amor (ICTAI, 2014)

A Personalized Recommender System from Probabilistic Relational Model and Users' Preferences. - Rajani Chulyadyo; Philippe Leray 001 (KES, 2014)

Implicit parameter estimation for conditional Gaussian Bayesian networks. - Aida Jarraya; Philippe Leray 001; Afif Masmoudi (Int. J. Comput. Intell. Syst., 2014)

Discrete exponential Bayesian networks: Definition, learning and application for density estimation. - Aida Jarraya; Philippe Leray 001; Afif Masmoudi (Neurocomputing, 2014)

Modeling Genetical Data with Forests of Latent Trees for Applications in Association Genetics at a Large Scale - Which Clustering Method should Be Chosen?. - Duc-Thanh Phan; Philippe Leray 001; Christine Sinoquet (BIOINFORMATICS, 2015)

Latent Forests to Model Genetical Data for the Purpose of Multilocus Genome-Wide Association Studies. Which Clustering Should Be Chosen? - Duc-Thanh Phan; Philippe Leray 001; Christine Sinoquet (BIOSTEC (Selected Papers), 2015)

Integrating spatial information into probabilistic relational models. - Rajani Chulyadyo; Philippe Leray 001 (DSAA, 2015)

Evaluating Product-Based Possibilistic Networks Learning Algorithms. - Maroua Haddad 001; Philippe Leray 001; Nahla Ben Amor (ECSQARU, 2015)

CPD Tree Learning Using Contexts as Background Knowledge. - Gérard Ramstein; Philippe Leray 001 (ECSQARU, 2015)

On the equivalence between regularized NMF and similarity-augmented graph partitioning. - Anthony Coutant; Hoel Le Capitaine; Philippe Leray 001 (ESANN, 2015)

Learning possibilistic networks from data: a survey. - Maroua Haddad 001; Philippe Leray 001; Nahla Ben Amor (IFSA-EUSFLAT, 2015)

Probabilistic Relational Models with clustering uncertainty. - Anthony Coutant; Philippe Leray 001; Hoel Le Capitaine (IJCNN, 2015)

SemCaDo: A serendipitous strategy for causal discovery and ontology evolution. - Montassar Ben Messaoud; Philippe Leray 001; Nahla Ben Amor (Knowl. Based Syst., 2015)

Apprentissage des réseaux possibilistes à partir de données. - Maroua Haddad 001; Philippe Leray 001; Nahla Ben Amor (Rev. d'Intelligence Artif., 2015)

Introduction. - Philippe Leray 001; Grégory Nuel (Rev. d'Intelligence Artif., 2015)

A Hybrid Approach for Probabilistic Relational Models Structure Learning. - Mouna Ben Ishak; Philippe Leray 001; Nahla Ben Amor (IDA, 2016)

An Exact Approach to Learning Probabilistic Relational Model. - Nourhene Ettouzi; Philippe Leray 001; Montassar Ben Messaoud (Probabilistic Graphical Models, 2016)

Possibilistic Networks: Parameters Learning from Imprecise Data and Evaluation strategy. - Maroua Haddad 001; Philippe Leray 001; Nahla Ben Amor (CoRR, 2016)

Probabilistic Relational Model Benchmark Generation. - Mouna Ben Ishak; Rajani Chulyadyo; Philippe Leray 001 (CoRR, 2016)

Probabilistic relational model benchmark generation: Principle and application. - Mouna Ben Ishak; Philippe Leray 001; Nahla Ben Amor (Intell. Data Anal., 2016)

Learning Probabilistic Relational Models with (Partially Structured) Graph Databases. - Marwa El Abri; Philippe Leray 001; Nadia Essoussi (AICCSA, 2017)

Customer Relationship Management and Small Data - Application of Bayesian Network Elicitation Techniques for Building a Lead Scoring Model. - Youssef Benhaddou; Philippe Leray 001 (AICCSA, 2017)

Possibilistic MDL: A New Possibilistic Likelihood Based Score Function for Imprecise Data. - Maroua Haddad 001; Philippe Leray 001; Nahla Ben Amor (ECSQARU, 2017)

Learning the Parameters of Possibilistic Networks from Data: Empirical Comparison. - Maroua Haddad 001; Philippe Leray 001; Amélie Levray; Karim Tabia (FLAIRS, 2017)

A Probabilistic Relational Model Approach for Fault Tree Modeling. - Thierno Kanté; Philippe Leray 001 (IEA/AIE (2), 2017)

On the Use of WalkSAT Based Algorithms for MLN Inference in Some Realistic Applications. - Romain Rincé; Romain Kervarc; Philippe Leray 001 (IEA/AIE (2), 2017)

DAPER Joint Learning from Partially Structured Graph Databases. - Marwa El Abri; Philippe Leray 001; Nadia Essoussi (ICDEc, 2018)

Using Probabilistic Relational Models to generate synthetic spatial or non-spatial databases. - Rajani Chulyadyo; Philippe Leray 001 (RCIS, 2018)

Complex Event Processing Under Uncertainty Using Markov Chains, Constraints, and Sampling. - Romain Rincé; Romain Kervarc; Philippe Leray 001 (RuleML+RR, 2018)

Qualitative Probabilistic Relational Models. - Linda C. van der Gaag; Philippe Leray 001 (SUM, 2018)

Relational Constraints for Metric Learning on Relational Data. - Jiajun Pan; Hoel Le Capitaine; Philippe Leray 001 (CoRR, 2018)

Multi-task Transfer Learning for Timescale Graphical Event Models. - Mathilde Monvoisin; Philippe Leray 001 (ECSQARU, 2019)

Graphical Event Model Learning and Verification for Security Assessment. - Dimitri Antakly; Benoît Delahaye; Philippe Leray 001 (IEA/AIE, 2019)

A Probabilistic Relational Model for Risk Assessment and Spatial Resources Management. - Thierno Kanté; Philippe Leray 001 (IEA/AIE, 2019)

On Intercausal Interactions in Probabilistic Relational Models. - Silja Renooij; Linda C. van der Gaag; Philippe Leray 001 (ISIPTA, 2019)

Belief Graphical Models for Uncertainty Representation and Reasoning. - Salem Benferhat; Philippe Leray 001; Karim Tabia (A Guided Tour of Artificial Intelligence Research (2) (II), 2020)

Interactive Anomaly Detection in Mixed Tabular Data using Bayesian Networks. - Evan Dufraisse; Philippe Leray 001; Raphaël Nedellec; Tarek Benkhelif (PGM, 2020)

Integrating expert's knowledge constraint of time dependent exposures in structure learning for Bayesian networks. - Vahé Asvatourian; Philippe Leray 001; Stefan Michiels; Emilie Lanoy (Artif. Intell. Medicine, 2020)

Multi-task Transfer Learning for Bayesian Network Structures. - Sarah Benikhlef; Philippe Leray 001; Guillaume Raschia; Montassar Ben Messaoud; Fayrouz Sakly (ECSQARU, 2021)

Unsupervised Co-training of Bayesian Networks for Condition Prediction. - Mathilde Monvoisin; Philippe Leray 001; Mathieu Ritou (IEA/AIE (2), 2021)

Iterative knowledge discovery for fault detection in manufacturing systems. - Mahmoud Ferhat; Philippe Leray 001; Mathieu Ritou; Nicolas Le Du (KES, 2022)

An Optimized Quantum Circuit Representation of Bayesian Networks. - Walid Fathallah; Nahla Ben Amor; Philippe Leray 001 (ECSQARU, 2023)

Mining Discriminative Sequential Patterns of Self-regulated Learners. - Amine Boulahmel; Fahima Djelil; Jean-Marie Gilliot; Philippe Leray 001; Grégory Smits (ITS (2), 2024)

Approximate inference on optimized quantum Bayesian networks. - Walid Fathallah; Nahla Ben Amor; Philippe Leray 001 (Int. J. Approx. Reason., 2024)

Predicting spotify audio features from Last.fm tags. - Jaime Ramírez Castillo; M. Julia Flores; Philippe Leray 001 (Multim. Tools Appl., 2024)