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Pierre-Henri Wuillemin
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2020 – today
- 2024
- [j17]Mahdi Hadj Ali
, Yann Le Biannic, Pierre-Henri Wuillemin:
Reliable Estimation of Causal Effects Using Predictive Models. Int. J. Artif. Intell. Tools 33(3): 2460006:1-2460006:33 (2024) - [c47]Mahdi Hadj Ali, Yann Le Biannic, Pierre-Henri Wuillemin
Quantifying a Causal Effect from a CPDAG with Targeted Exogenous Causal Knowledge. ECAI 2024: 3187-3194 - 2023
- [j16]Bastien Chassagnol, Antoine Bichat
Gaussian Mixture Models in R. R J. 15(2): 56-76 (2023) - [c46]Chen Dang, Cristina Bazgan, Tristan Cazenave, Morgan Chopin, Pierre-Henri Wuillemin:
Warm-Starting Nested Rollout Policy Adaptation with Optimal Stopping. AAAI 2023: 12381-12389 - [c45]Mahdi Hadj Ali
Interpreting Predictive Models through Causality: A Query-Driven Methodology. FLAIRS 2023 - [c44]Clara Charon
Improving Pressure Ulcers Prediction in Nursing Homes with ML Algorithm. MIE 2023: 350-351 - 2022
- [j15]Mélanie Münch
Combining ontology and probabilistic models for the design of bio-based product transformation processes. Expert Syst. Appl. 203: 117406 (2022) - [j14]Melanie Munch, Patrice Buche, Hélène Angellier-Coussy, Cristina E. Manfredotti, Pierre-Henri Wuillemin:
Formalising contextual expert knowledge for causal discovery in linked knowledge graphs about transformation processes: application to processing of bio-composites for food packaging. Int. J. Metadata Semant. Ontologies 16(1): 1-15 (2022) - [c43]Clara Charon
Learning Bayesian Networks for the Prediction of Unfavorable Health Events in Nursing Homes. MIE 2022: 147-148 - 2021
- [j13]Marvin Lasserre
Constraint-based learning for non-parametric continuous bayesian networks. Ann. Math. Artif. Intell. 89(10-11): 1035-1052 (2021) - [j12]Nataliya Sokolovska
The Role of Instrumental Variables in Causal Inference Based on Independence of Cause and Mechanism. Entropy 23(8): 928 (2021) - [c42]Marvin Lasserre, Régis Lebrun, Pierre-Henri Wuillemin:
Learning Continuous High-Dimensional Models using Mutual Information and Copula Bayesian Networks. AAAI 2021: 12139-12146 - [c41]Mélanie Münch
A Process Reverse Engineering Approach Using Process and Observation Ontology and Probabilistic Relational Models: Application to Processing of Bio-composites for Food Packaging. MTSR 2021: 3-15 - [c40]Chen Dang
Monte Carlo Search Algorithms for Network Traffic Engineering. ECML/PKDD (4) 2021: 486-501 - 2020
- [c39]Marvin Lasserre, Régis Lebrun, Pierre-Henri Wuillemin:
Constaint-Based Learning for Non-Parametric Continuous Bayesian Networks. FLAIRS 2020: 581-586 - [c38]Gaspard Ducamp, Philippe Bonnard, Pierre-Henri Wuillemin:
Uncertain Reasoning in Rule-Based Systems Using PRM. FLAIRS 2020: 617-620 - [c37]Gaspard Ducamp, Philippe Bonnard, Anthony Nouy, Pierre-Henri Wuillemin:
An Efficient Low-Rank Tensors Representation for Algorithms in Complex Probabilistic Graphical Models. PGM 2020: 173-184 - [c36]Gaspard Ducamp, Christophe Gonzales, Pierre-Henri Wuillemin:
aGrUM/pyAgrum : a toolbox to build models and algorithms for Probabilistic Graphical Models in Python. PGM 2020: 609-612 - [c35]Gaspard Ducamp, Philippe Bonnard, Christian de Sainte Marie, Pierre-Henri Wuillemin:
Advanced Syntax and Compilation for Probabilistic Production Rules with PRM. RuleML+RR (Supplement) 2020: 103-110 - [i3]Nataliya Sokolovska, Pierre-Henri Wuillemin
Latent Instrumental Variables as Priors in Causal Inference based on Independence of Cause and Mechanism. CoRR abs/2007.08812 (2020)
2010 – 2019
- 2019
- [c34]Melanie Munch, Juliette Dibie, Pierre-Henri Wuillemin, Cristina E. Manfredotti:
Towards Interactive Causal Relation Discovery Driven by an Ontology. FLAIRS 2019: 504-508 - [c33]Melanie Munch, Juliette Dibie-Barthélemy, Pierre-Henri Wuillemin, Cristina E. Manfredotti:
Interactive Causal Discovery in Knowledge Graphs. PROFILES/SEMEX@ISWC 2019: 78-93 - 2018
- [j11]Véronique Delcroix, Pierre-Henri Wuillemin:
Introduction. Rev. d'Intelligence Artif. 32(1): 7-10 (2018) - [j10]Matthieu Hourbracq, Pierre-Henri Wuillemin, Christophe Gonzales, Philippe Baumard:
Apprentissage et sélection de réseaux bayésiens dynamiques pour les processus online non stationnaires. Rev. d'Intelligence Artif. 32(1): 75-109 (2018) - [j9]Hamza Agli, Philippe Bonnard, Christophe Gonzales, Pierre-Henri Wuillemin:
Inférence incrémentale pour les modèles. Rev. d'Intelligence Artif. 32(1): 111-132 (2018) - [c32]Melanie Munch
Identifying Control Parameters in Cheese Fabrication Process Using Precedence Constraints. DS 2018: 421-434 - [c31]Miyoung Han, Pierre-Henri Wuillemin
Focused Crawling Through Reinforcement Learning. ICWE 2018: 261-278 - [c30]Gaspard Ducamp, Philippe Bonnard, Christian de Sainte Marie, Christophe Gonzales, Pierre-Henri Wuillemin:
Improving Probabilistic Rules Compilation using PRM. RuleML+RR (Supplement) 2018 - 2017
- [j8]Jean-Christophe Magnan, Pierre-Henri Wuillemin
Efficient incremental planning and learning with multi-valued decision diagrams. J. Appl. Log. 22: 63-90 (2017) - [j7]Lom-Messan Hillah, Ariele-Paolo Maesano, Fabio De Rosa, Fabrice Kordon, Pierre-Henri Wuillemin
Automation and intelligent scheduling of distributed system functional testing - Model-based functional testing in practice. Int. J. Softw. Tools Technol. Transf. 19(3): 281-308 (2017) - [c29]Matthieu Hourbracq, Pierre-Henri Wuillemin, Christophe Gonzales, Philippe Baumard:
Learning and Selection of Dynamic Bayesian Networks for Non-Stationary Processes in Real Time. FLAIRS 2017: 742-747 - [c28]Christophe Gonzales, Lionel Torti, Pierre-Henri Wuillemin
aGrUM: A Graphical Universal Model Framework. IEA/AIE (2) 2017: 171-177 - [c27]Melanie Munch
Learning Probabilistic Relational Models Using an Ontology of Transformation Processes. OTM Conferences (2) 2017: 198-215 - 2016
- [j6]Cédric Baudrit, Sébastien Destercke
Unifying parameter learning and modelling complex systems with epistemic uncertainty using probability interval. Inf. Sci. 367-368: 630-647 (2016) - [c26]Hamza Agli, Philippe Bonnard, Christophe Gonzales, Pierre-Henri Wuillemin
Incremental Junction Tree Inference. IPMU (1) 2016: 326-337 - [c25]Matthieu Hourbracq, Pierre-Henri Wuillemin
Real Time Learning of Non-stationary Processes with Dynamic Bayesian Networks. IPMU (1) 2016: 338-350 - [c24]Hamza Agli, Philippe Bonnard, Christophe Gonzales, Pierre-Henri Wuillemin
Business Rules Uncertainty Management with Probabilistic Relational Models. RuleML 2016: 53-67 - [c23]Lom-Messan Hillah, Ariele-Paolo Maesano, Libero Maesano, Fabio De Rosa, Fabrice Kordon, Pierre-Henri Wuillemin:
Service functional testing automation with intelligent scheduling and planning. SAC 2016: 1605-1610 - 2015
- [j5]Jean-Baptiste Rouquier, Isabelle Alvarez, Romain Reuillon, Pierre-Henri Wuillemin
A kd-tree algorithm to discover the boundary of a black box hypervolume - Or how to peel potatoes by recursively cutting them in halves. Ann. Math. Artif. Intell. 75(3-4): 335-350 (2015) - [c22]Yang Chen, Pierre-Henri Wuillemin, Jean-Marc Labat:
Discovering Prerequisite Structure of Skills through Probabilistic Association Rules Mining. EDM 2015: 117-124 - [c21]Jean-Christophe Magnan, Pierre-Henri Wuillemin:
On-Line Learning of Multi-Valued Decision Diagrams. FLAIRS 2015: 576-580 - [c20]Cristina E. Manfredotti
Mapping Ontology with Probabilistic Relational Models. KEOD 2015: 171-178 - [c19]Steffen Herbold
The MIDAS Cloud Platform for Testing SOA Applications. ICST 2015: 1-8 - 2014
- [c18]Yang Chen, Pierre-Henri Wuillemin
Bayesian Student Modeling Improved by Diagnostic Items. Intelligent Tutoring Systems 2014: 144-149 - [c17]Hamza Agli, Philippe Bonnard, Pierre-Henri Wuillemin, Christophe Gonzales:
Uncertain Reasoning for Business Rules. Challenge+DC@RuleML 2014 - 2013
- [j4]Lionel Torti, Christophe Gonzales, Pierre-Henri Wuillemin
Speeding-up structured probabilistic inference using pattern mining. Int. J. Approx. Reason. 54(7): 900-918 (2013) - [c16]Alberto Paolo Tonda, Evelyne Lutton
A Memetic Approach to Bayesian Network Structure Learning. EvoApplications 2013: 102-111 - [c15]Jean-Christophe Magnan, Pierre-Henri Wuillemin:
Improving Decision Diagrams for Decision Theoretic Planning. FLAIRS 2013 - [p1]Olivier Barrière
Cooperative Coevolution for Agrifood Process Modeling. EVOLVE 2013: 247-287 - [i2]Thomas D. Nielsen, Pierre-Henri Wuillemin, Finn Verner Jensen, Uffe Kjærulff:
Using ROBDDs for Inference in Bayesian Networks with Troubleshooting as an Example. CoRR abs/1301.3880 (2013) - 2012
- [j3]Pierre-Henri Wuillemin
Structured probabilistic inference. Int. J. Approx. Reason. 53(7): 946-968 (2012) - [c14]Alberto Paolo Tonda
Bayesian Network Structure Learning from Limited Datasets through Graph Evolution. EuroGP 2012: 254-265 - [i1]Thomas Degris, Olivier Sigaud, Pierre-Henri Wuillemin:
Chi-square Tests Driven Method for Learning the Structure of Factored MDPs. CoRR abs/1206.6842 (2012) - 2011
- [j2]Mariette Sicard, Cédric Baudrit, M. N. Leclerc-Perlat, Pierre-Henri Wuillemin
Expert knowledge integration to model complex food processes. Application on the camembert cheese ripening process. Expert Syst. Appl. 38(9): 11804-11812 (2011) - [c13]Lionel Torti, Christophe Gonzales, Pierre-Henri Wuillemin
Patterns Discovery for Efficient Structured Probabilistic Inference. SUM 2011: 247-260 - 2010
- [c12]Lionel Torti, Pierre-Henri Wuillemin:
Structured Value Elimination with D-Separation Analysis. FLAIRS 2010 - [c11]Ettarres Yamna, Khaled Mellouli, Pierre-Henri Wuillemin:
A Multicriteria Bayesian Intelligent Tutoring System MBITS. ISDA 2010: 714-719
2000 – 2009
- 2009
- [j1]Thomas Degris, Olivier Sigaud, Pierre-Henri Wuillemin:
Apprentissage par renforcement factorisé pour le comportement de personnages non joueurs. Rev. d'Intelligence Artif. 23(2-3): 221-251 (2009) - [c10]Olivier Barrière
Bayesian network structure learning using cooperative coevolution. GECCO 2009: 755-762 - [c9]Olga Kozlova, Olivier Sigaud, Pierre-Henri Wuillemin
Considering Unseen States as Impossible in Factored Reinforcement Learning. ECML/PKDD (1) 2009: 721-735 - 2008
- [c8]Thomas Degris, Olivier Sigaud, Pierre-Henri Wuillemin
Exploiting Additive Structure in Factored MDPs for Reinforcement Learning. EWRL 2008: 15-26 - [c7]Cédric Baudrit, Pierre-Henri Wuillemin
A Dynamic Bayesian Network to Represent a Ripening Process of a Soft Mould Cheese. KES (2) 2008: 265-272 - 2006
- [c6]Thomas Degris, Olivier Sigaud, Pierre-Henri Wuillemin
Learning the structure of Factored Markov Decision Processes in reinforcement learning problems. ICML 2006: 257-264 - [c5]Thomas Degris, Olivier Sigaud, Pierre-Henri Wuillemin:
Chi-square Tests Driven Method for Learning the Structure of Factored MDPs. UAI 2006 - 2004
- [c4]Olivier Sigaud, Thierry Gourdin, Pierre-Henri Wuillemin
Improving MACS Thanks to a Comparison with 2TBNs. GECCO (2) 2004: 810-823 - 2000
- [c3]Olav Bangsø, Pierre-Henri Wuillemin:
Top-Down Construction and Repetetive Structures Representation in Bayesian Networks. FLAIRS 2000: 282-286 - [c2]Pierre-Henri Wuillemin, Olav Bangsø:
Réseaux Probabilistes Orientés Objet. LMO 2000: 123-138 - [c1]Thomas D. Nielsen, Pierre-Henri Wuillemin, Finn Verner Jensen, Uffe Kjærulff:
Using ROBDDs for Inference in Bayesian Networks with Troubleshooting as an Example. UAI 2000: 426-435
Coauthor Index
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last updated on 2024-11-07 21:28 CET by the dblp team
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