Pierre-Henri Wuillemin

According to our database1, Pierre-Henri Wuillemin authored at least 46 papers between 2000 and 2019.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.



In proceedings 
PhD thesis 


On csauthors.net:


Interactive Causal Discovery in Knowledge Graphs.
Proceedings of the Joint Proceedings of the 6th International Workshop on Dataset PROFlLing and Search & the 1st Workshop on Semantic Explainability co-located with the 18th International Semantic Web Conference (ISWC 2019), 2019

Towards Interactive Causal Relation Discovery Driven by an Ontology.
Proceedings of the Thirty-Second International Florida Artificial Intelligence Research Society Conference, 2019

Apprentissage et sélection de réseaux bayésiens dynamiques pour les processus online non stationnaires.
Revue d'Intelligence Artificielle, 2018

Revue d'Intelligence Artificielle, 2018

Inférence incrémentale pour les modèles.
Revue d'Intelligence Artificielle, 2018

Improving Probabilistic Rules Compilation using PRM.
Proceedings of the Doctoral Consortium and Challenge @ RuleML+RR 2018 hosted by 2nd International Joint Conference on Rules and Reasoning (RuleML+RR 2018), 2018

Focused Crawling Through Reinforcement Learning.
Proceedings of the Web Engineering - 18th International Conference, 2018

Identifying Control Parameters in Cheese Fabrication Process Using Precedence Constraints.
Proceedings of the Discovery Science - 21st International Conference, 2018

Automation and intelligent scheduling of distributed system functional testing - Model-based functional testing in practice.
STTT, 2017

Efficient incremental planning and learning with multi-valued decision diagrams.
J. Appl. Log., 2017

Learning Probabilistic Relational Models Using an Ontology of Transformation Processes.
Proceedings of the On the Move to Meaningful Internet Systems. OTM 2017 Conferences, 2017

aGrUM: A Graphical Universal Model Framework.
Proceedings of the Advances in Artificial Intelligence: From Theory to Practice, 2017

Learning and Selection of Dynamic Bayesian Networks for Non-Stationary Processes in Real Time.
Proceedings of the Thirtieth International Florida Artificial Intelligence Research Society Conference, 2017

Unifying parameter learning and modelling complex systems with epistemic uncertainty using probability interval.
Inf. Sci., 2016

Service functional testing automation with intelligent scheduling and planning.
Proceedings of the 31st Annual ACM Symposium on Applied Computing, 2016

Business Rules Uncertainty Management with Probabilistic Relational Models.
Proceedings of the Rule Technologies. Research, Tools, and Applications, 2016

Real Time Learning of Non-stationary Processes with Dynamic Bayesian Networks.
Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems, 2016

Incremental Junction Tree Inference.
Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems, 2016

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., 2015

The MIDAS Cloud Platform for Testing SOA Applications.
Proceedings of the 8th IEEE International Conference on Software Testing, 2015

Mapping Ontology with Probabilistic Relational Models.
Proceedings of the KEOD 2015, 2015

On-Line Learning of Multi-Valued Decision Diagrams.
Proceedings of the Twenty-Eighth International Florida Artificial Intelligence Research Society Conference, 2015

Discovering Prerequisite Structure of Skills through Probabilistic Association Rules Mining.
Proceedings of the 8th International Conference on Educational Data Mining, 2015

Uncertain Reasoning for Business Rules.
Proceedings of the RuleML 2014 Challenge and the RuleML 2014 Doctoral Consortium hosted by the 8th International Web Rule Symposium, 2014

Bayesian Student Modeling Improved by Diagnostic Items.
Proceedings of the Intelligent Tutoring Systems - 12th International Conference, 2014

Cooperative Coevolution for Agrifood Process Modeling.
Proceedings of the EVOLVE, 2013

Speeding-up structured probabilistic inference using pattern mining.
Int. J. Approx. Reason., 2013

Improving Decision Diagrams for Decision Theoretic Planning.
Proceedings of the Twenty-Sixth International Florida Artificial Intelligence Research Society Conference, 2013

A Memetic Approach to Bayesian Network Structure Learning.
Proceedings of the Applications of Evolutionary Computation - 16th European Conference, 2013

Structured probabilistic inference.
Int. J. Approx. Reason., 2012

Bayesian Network Structure Learning from Limited Datasets through Graph Evolution.
Proceedings of the Genetic Programming - 15th European Conference, 2012

Expert knowledge integration to model complex food processes. Application on the camembert cheese ripening process.
Expert Syst. Appl., 2011

Patterns Discovery for Efficient Structured Probabilistic Inference.
Proceedings of the Scalable Uncertainty Management - 5th International Conference, 2011

A Multicriteria Bayesian Intelligent Tutoring System MBITS.
Proceedings of the 10th International Conference on Intelligent Systems Design and Applications, 2010

Structured Value Elimination with D-Separation Analysis.
Proceedings of the Twenty-Third International Florida Artificial Intelligence Research Society Conference, 2010

Apprentissage par renforcement factorisé pour le comportement de personnages non joueurs.
Revue d'Intelligence Artificielle, 2009

Considering Unseen States as Impossible in Factored Reinforcement Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2009

Bayesian network structure learning using cooperative coevolution.
Proceedings of the Genetic and Evolutionary Computation Conference, 2009

A Dynamic Bayesian Network to Represent a Ripening Process of a Soft Mould Cheese.
Proceedings of the Knowledge-Based Intelligent Information and Engineering Systems, 2008

Exploiting Additive Structure in Factored MDPs for Reinforcement Learning.
Proceedings of the Recent Advances in Reinforcement Learning, 8th European Workshop, 2008

Chi-square Tests Driven Method for Learning the Structure of Factored MDPs.
Proceedings of the UAI '06, 2006

Learning the structure of Factored Markov Decision Processes in reinforcement learning problems.
Proceedings of the Machine Learning, 2006

Improving MACS Thanks to a Comparison with 2TBNs.
Proceedings of the Genetic and Evolutionary Computation, 2004

Using ROBDDs for Inference in Bayesian Networks with Troubleshooting as an Example.
Proceedings of the UAI '00: Proceedings of the 16th Conference in Uncertainty in Artificial Intelligence, Stanford University, Stanford, California, USA, June 30, 2000

Réseaux Probabilistes Orientés Objet.
Proceedings of the Actes des journées Langages et Modèles à Objets, 2000

Top-Down Construction and Repetetive Structures Representation in Bayesian Networks.
Proceedings of the Thirteenth International Florida Artificial Intelligence Research Society Conference, 2000