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Philippe Leray 0001
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- affiliation: Ecole Polytechnique de l'université de Nantes, France
Other persons with the same name
- Philippe Leray 0002 — imec, Leuven, Belgium
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2020 – today
- 2024
- [j19]Walid Fathallah
, Nahla Ben Amor, Philippe Leray:
Approximate inference on optimized quantum Bayesian networks. Int. J. Approx. Reason. 175: 109307 (2024) - [j18]Jaime Ramírez Castillo, M. Julia Flores
Predicting spotify audio features from Last.fm tags. Multim. Tools Appl. 83(16): 48311-48330 (2024) - [c70]Amine Boulahmel
Mining Discriminative Sequential Patterns of Self-regulated Learners. ITS (2) 2024: 137-149 - 2023
- [c69]Walid Fathallah
An Optimized Quantum Circuit Representation of Bayesian Networks. ECSQARU 2023: 160-171 - 2022
- [c68]Mahmoud Ferhat, Philippe Leray, Mathieu Ritou, Nicolas Le Du:
Iterative knowledge discovery for fault detection in manufacturing systems. KES 2022: 744-753 - 2021
- [c67]Sarah Benikhlef, Philippe Leray
Multi-task Transfer Learning for Bayesian Network Structures. ECSQARU 2021: 217-228 - [c66]Mathilde Monvoisin, Philippe Leray
Unsupervised Co-training of Bayesian Networks for Condition Prediction. IEA/AIE (2) 2021: 577-588 - 2020
- [j17]Vahé Asvatourian, Philippe Leray
Integrating expert's knowledge constraint of time dependent exposures in structure learning for Bayesian networks. Artif. Intell. Medicine 107: 101874 (2020) - [c65]Evan Dufraisse, Philippe Leray, Raphaël Nedellec, Tarek Benkhelif:
Interactive Anomaly Detection in Mixed Tabular Data using Bayesian Networks. PGM 2020: 185-196 - [p2]Salem Benferhat, Philippe Leray, Karim Tabia:
Belief Graphical Models for Uncertainty Representation and Reasoning. A Guided Tour of Artificial Intelligence Research (2) (II) 2020: 209-246
2010 – 2019
- 2019
- [c64]Mathilde Monvoisin, Philippe Leray
Multi-task Transfer Learning for Timescale Graphical Event Models. ECSQARU 2019: 313-323 - [c63]Dimitri Antakly, Benoît Delahaye
Graphical Event Model Learning and Verification for Security Assessment. IEA/AIE 2019: 245-252 - [c62]Thierno Kanté, Philippe Leray
A Probabilistic Relational Model for Risk Assessment and Spatial Resources Management. IEA/AIE 2019: 555-563 - [c61]Silja Renooij, Linda C. van der Gaag, Philippe Leray:
On Intercausal Interactions in Probabilistic Relational Models. ISIPTA 2019: 327-329 - 2018
- [c60]Marwa El Abri, Philippe Leray
DAPER Joint Learning from Partially Structured Graph Databases. ICDEc 2018: 129-138 - [c59]Rajani Chulyadyo, Philippe Leray
Using Probabilistic Relational Models to generate synthetic spatial or non-spatial databases. RCIS 2018: 1-12 - [c58]Romain Rincé, Romain Kervarc, Philippe Leray
Complex Event Processing Under Uncertainty Using Markov Chains, Constraints, and Sampling. RuleML+RR 2018: 147-163 - [c57]Linda C. van der Gaag, Philippe Leray
Qualitative Probabilistic Relational Models. SUM 2018: 276-289 - [i4]Jiajun Pan, Hoel Le Capitaine, Philippe Leray:
Relational Constraints for Metric Learning on Relational Data. CoRR abs/1807.00558 (2018) - 2017
- [c56]Youssef Benhaddou, Philippe Leray
Customer Relationship Management and Small Data - Application of Bayesian Network Elicitation Techniques for Building a Lead Scoring Model. AICCSA 2017: 251-255 - [c55]Marwa El Abri, Philippe Leray
Learning Probabilistic Relational Models with (Partially Structured) Graph Databases. AICCSA 2017: 256-263 - [c54]Maroua Haddad
Possibilistic MDL: A New Possibilistic Likelihood Based Score Function for Imprecise Data. ECSQARU 2017: 435-445 - [c53]Maroua Haddad, Philippe Leray, Amélie Levray, Karim Tabia:
Learning the Parameters of Possibilistic Networks from Data: Empirical Comparison. FLAIRS 2017: 736-741 - [c52]Romain Rincé, Romain Kervarc, Philippe Leray
On the Use of WalkSAT Based Algorithms for MLN Inference in Some Realistic Applications. IEA/AIE (2) 2017: 121-131 - [c51]Thierno Kanté, Philippe Leray
A Probabilistic Relational Model Approach for Fault Tree Modeling. IEA/AIE (2) 2017: 154-162 - 2016
- [j16]Mouna Ben Ishak, Philippe Leray
Probabilistic relational model benchmark generation: Principle and application. Intell. Data Anal. 20(3): 615-635 (2016) - [c50]Mouna Ben Ishak, Philippe Leray
A Hybrid Approach for Probabilistic Relational Models Structure Learning. IDA 2016: 38-49 - [c49]Nourhene Ettouzi, Philippe Leray, Montassar Ben Messaoud:
An Exact Approach to Learning Probabilistic Relational Model. Probabilistic Graphical Models 2016: 171-182 - [i3]Mouna Ben Ishak, Rajani Chulyadyo, Philippe Leray:
Probabilistic Relational Model Benchmark Generation. CoRR abs/1603.00709 (2016) - [i2]Maroua Haddad, Philippe Leray, Nahla Ben Amor:
Possibilistic Networks: Parameters Learning from Imprecise Data and Evaluation strategy. CoRR abs/1607.03705 (2016) - 2015
- [j15]Montassar Ben Messaoud
SemCaDo: A serendipitous strategy for causal discovery and ontology evolution. Knowl. Based Syst. 76: 79-95 (2015) - [j14]Philippe Leray, Grégory Nuel:
Introduction. Rev. d'Intelligence Artif. 29(2): 149-151 (2015) - [j13]Maroua Haddad
Apprentissage des réseaux possibilistes à partir de données. Rev. d'Intelligence Artif. 29(2): 229-252 (2015) - [c48]Duc-Thanh Phan, Philippe Leray, Christine Sinoquet:
Modeling Genetical Data with Forests of Latent Trees for Applications in Association Genetics at a Large Scale - Which Clustering Method should Be Chosen?. BIOINFORMATICS 2015: 5-16 - [c47]Duc-Thanh Phan, Philippe Leray
Latent Forests to Model Genetical Data for the Purpose of Multilocus Genome-Wide Association Studies. Which Clustering Should Be Chosen? BIOSTEC (Selected Papers) 2015: 169-189 - [c46]Rajani Chulyadyo, Philippe Leray
Integrating spatial information into probabilistic relational models. DSAA 2015: 1-8 - [c45]Maroua Haddad
Evaluating Product-Based Possibilistic Networks Learning Algorithms. ECSQARU 2015: 312-321 - [c44]Gérard Ramstein
CPD Tree Learning Using Contexts as Background Knowledge. ECSQARU 2015: 356-365 - [c43]Anthony Coutant, Hoel Le Capitaine, Philippe Leray:
On the equivalence between regularized NMF and similarity-augmented graph partitioning. ESANN 2015 - [c42]Maroua Haddad, Philippe Leray, Nahla Ben Amor:
Learning possibilistic networks from data: a survey. IFSA-EUSFLAT 2015 - [c41]Anthony Coutant, Philippe Leray
Probabilistic Relational Models with clustering uncertainty. IJCNN 2015: 1-8 - 2014
- [j12]Aida Jarraya, Philippe Leray
Implicit parameter estimation for conditional Gaussian Bayesian networks. Int. J. Comput. Intell. Syst. 7(sup1): 6-17 (2014) - [j11]Aida Jarraya, Philippe Leray
Discrete exponential Bayesian networks: Definition, learning and application for density estimation. Neurocomputing 137: 142-149 (2014) - [c40]Anthony Coutant, Philippe Leray, Hoel Le Capitaine:
Learning Probabilistic Relational Models Using Non-Negative Matrix Factorization. FLAIRS 2014 - [c39]Aymeric Le Dorze, Béatrice Duval, Laurent Garcia, David Genest, Philippe Leray, Stéphane Loiseau:
Probabilistic Cognitive Maps - Semantics of a Cognitive Map when the Values are Assumed to be Probabilities. ICAART (1) 2014: 52-62 - [c38]Aymeric Le Dorze, Béatrice Duval, Laurent Garcia, David Genest, Philippe Leray
A Probabilistic Semantics for Cognitive Maps. ICAART (Revised Selected Papers) 2014: 151-169 - [c37]Philippe Leray:
Advances in Learning with Bayesian Networks. ICAART (1) 2014: IS-5 - [c36]Mouna Ben Ishak, Philippe Leray, Nahla Ben Amor
Random Generation and Population of Probabilistic Relational Models and Databases. ICTAI 2014: 756-763 - [c35]Rajani Chulyadyo, Philippe Leray
A Personalized Recommender System from Probabilistic Relational Model and Users' Preferences. KES 2014: 1063-1072 - [i1]Raphaël Mourad, Christine Sinoquet, Nevin Lianwen Zhang, Tengfei Liu, Philippe Leray:
A Survey on Latent Tree Models and Applications. CoRR abs/1402.0577 (2014) - 2013
- [j10]Salem Benferhat, Philippe Leray
Editorial: Uncertainty in Artificial Intelligence and Databases. Int. J. Approx. Reason. 54(7): 825-826 (2013) - [j9]Raphaël Mourad, Christine Sinoquet, Nevin Lianwen Zhang
A Survey on Latent Tree Models and Applications. J. Artif. Intell. Res. 47: 157-203 (2013) - [c34]Ghada Trabelsi, Philippe Leray
Dynamic MMHC: A Local Search Algorithm for Dynamic Bayesian Network Structure Learning. IDA 2013: 392-403 - [c33]Montassar Ben Messaoud
Active learning of causal Bayesian networks using ontologies: A case study. IJCNN 2013: 1-8 - [c32]Maroua Haddad
Imputation of Possibilistic Data for Structural Learning of Directed Acyclic Graphs. WILF 2013: 68-76 - 2012
- [j8]Raphaël Mourad, Christine Sinoquet, Philippe Leray
Probabilistic graphical models for genetic association studies. Briefings Bioinform. 13(1): 20-33 (2012) - [c31]Christine Sinoquet, Raphaël Mourad, Philippe Leray:
Forests of Latent Tree Models for the Detection of Genetic Associations. BIOINFORMATICS 2012: 5-14 - [c30]Christine Sinoquet, Raphaël Mourad, Philippe Leray
Forests of Latent Tree Models to Decipher Genotype-Phenotype Associations. BIOSTEC (Selected Papers) 2012: 113-134 - [c29]Amanullah Yasin, Philippe Leray:
iMMPC: Une approche locale pour l'apprentissage incrémental de la structure des réseaux bayésiens. EGC 2012: 587-588 - [c28]Aida Jarraya, Philippe Leray
Discrete Exponential Bayesian Networks Structure Learning for Density Estimation. ICIC (3) 2012: 146-151 - 2011
- [j7]Raphaël Mourad, Christine Sinoquet, Philippe Leray
A hierarchical Bayesian network approach for linkage disequilibrium modeling and data-dimensionality reduction prior to genome-wide association studies. BMC Bioinform. 12: 16 (2011) - [j6]Karim Tabia, Philippe Leray
Alert correlation: Severe attack prediction and controlling false alarm rate tradeoffs. Intell. Data Anal. 15(6): 955-978 (2011) - [c27]Montassar Ben Messaoud
SemCaDo: A Serendipitous Strategy for Learning Causal Bayesian Networks Using Ontologies. ECSQARU 2011: 182-193 - [c26]Sourour Ammar
Mixture of Markov Trees for Bayesian Network Structure Learning with Small Datasets in High Dimensional Space. ECSQARU 2011: 229-238 - [c25]Mouna Ben Ishak, Philippe Leray, Nahla Ben Amor:
A Two-way Approach for Probabilistic Graphical Models Structure Learning and Ontology Enrichment. KEOD 2011: 189-194 - [c24]Aida Jarraya, Philippe Leray
Discrete Exponential Bayesian Networks: An Extension of Bayesian Networks to Discrete Natural Exponential Families. ICTAI 2011: 205-208 - [c23]Amanullah Yasin, Philippe Leray
iMMPC: A Local Search Approach for Incremental Bayesian Network Structure Learning. IDA 2011: 401-412 - [c22]Hoai-Tuong Nguyen, Philippe Leray
Multiple Hypothesis Testing and Quasi Essential Graph for Comparing Two Sets of Bayesian Networks. KES (2) 2011: 176-185 - [c21]François Schnitzler
Efficiently Approximating Markov Tree Bagging for High-Dimensional Density Estimation. ECML/PKDD (3) 2011: 113-128 - 2010
- [j5]Roland Donat, Philippe Leray
A dynamic Bayesian network to represent discrete duration models. Neurocomputing 73(4-6): 570-577 (2010) - [c20]Raphaël Mourad, Christine Sinoquet, Philippe Leray:
Learning Hierarchical Bayesian Networks for Genome-Wide Association Studies. COMPSTAT 2010: 549-556 - [c19]François Schnitzler, Philippe Leray, Louis Wehenkel:
Towards sub-quadratic learning of probability density models in the form of mixtures of trees. ESANN 2010 - [c18]Karim Tabia, Philippe Leray
Bayesian Network-Based Approaches for Severe Attack Prediction and Handling IDSs' Reliability. IPMU (2) 2010: 632-642 - [c17]Karim Tabia, Philippe Leray:
Handling IDS' Reliability in Alert Correlation - A Bayesian Network-based Model for Handling IDS's Reliability and Controlling Prediction/False Alarm Rate Tradeoffs. SECRYPT 2010: 14-24
2000 – 2009
- 2009
- [c16]Sourour Ammar
Probability Density Estimation by Perturbing and Combining Tree Structured Markov Networks. ECSQARU 2009: 156-167 - [c15]Montassar Ben Messaoud
Integrating Ontological Knowledge for Iterative Causal Discovery and Visualization. ECSQARU 2009: 168-179 - 2008
- [c14]Roland Donat, Laurent Bouillaut, Patrice Aknin
Reliability Analysis using Graphical Duration Models. ARES 2008: 795-800 - [p1]Philippe Leray
Causal Graphical Models with Latent Variables: Learning and Inference. Innovations in Bayesian Networks 2008: 219-249 - 2007
- [j4]Philippe Leray:
Éditorial. Rev. d'Intelligence Artif. 21(3): 293-294 (2007) - [c13]Stijn Meganck, Philippe Leray, Bernard Manderick:
Causal Graphical Models with Latent Variables: Learning and Inference. ECSQARU 2007: 5-16 - [c12]Grégory Mallet, Philippe Leray, Hubert Polaert:
Méthodes statistiques et modèles thermiques compacts. EGC 2007: 213-214 - [c11]Olivier François
Generation of Incompliete Test-Data usinng Bayesinan Networks. IJCNN 2007: 2391-2396 - 2006
- [b1]Philippe Leray:
Réseaux bayésiens : Apprentissage et diagnostic de systemes complexes. University of Rouen, France, 2006 - [c10]Sam Maes, Philippe Leray
Multi-Agent Causal Models for Dependability Analysis. ARES 2006: 794-798 - [c9]Stijn Meganck, Philippe Leray
Learning Causal Bayesian Networks from Observations and Experiments: A Decision Theoretic Approach. MDAI 2006: 58-69 - [c8]Olivier François, Philippe Leray:
Learning the Tree Augmented Naive Bayes Classifier from incomplete datasets. Probabilistic Graphical Models 2006: 91-98 - [c7]Stijn Meganck, Sam Maes, Philippe Leray, Bernard Manderick:
Learning Semi-Markovian Causal Models using Experiments. Probabilistic Graphical Models 2006: 195-206 - 2005
- [c6]Stijn Meganck, Sam Maes, Bernard Manderick, Philippe Leray:
A Learning Algorithm for Multi-Agent Causal Models. EUMAS 2005: 190-201 - [c5]Ahmad Faour, Philippe Leray, Cédric Foll:
Réseaux bayésiens pour le filtrage d'alarmes dans les systèmes de détection d'intrusions. EGC (Ateliers) 2005: 69-72 - [c4]Olivier François, Philippe Leray:
Apprentissage de structure des réseaux bayésiens et données incomplètes. EGC 2005: 127-132 - [c3]Stijn Meganck, Sam Maes, Bernard Manderick, Philippe Leray
Distributed learning of Multi-Agent Causal Models. IAT 2005: 285-288 - 2004
- [j3]Iyad Zaarour, Laurent Heutte, Philippe Leray
Clustering And Bayesian Network Approaches For Discovering Handwriting Strategies Of Primary School Children. Int. J. Pattern Recognit. Artif. Intell. 18(7): 1233-1251 (2004) - [j2]Philippe Leray
Réseaux bayésiens pour la classification Méthodologie et illustration dans le cadre du diagnostic médical. Rev. d'Intelligence Artif. 18(2): 169-193 (2004) - [c2]Bruno Grilhères, Stephan Brunessaux, Philippe Leray:
Combining classifiers for harmful document filtering. RIAO 2004: 173-185 - 2001
- [j1]Philippe Leray
De l'utilisation d'OBD pour la sélection de variables dans les perceptrons multicouches. Rev. d'Intelligence Artif. 15(3-4): 373-391 (2001)
1990 – 1999
- 1996
- [c1]Philippe Leray
Diagnosis Tools for Telecommunication Network Traffic Management. ICANN 1996: 209-214
Coauthor Index
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