Pierre-Henri Wuillemin
Pierre-Henri Wuillemin
Sorbonne University
Verified email at - Homepage
Cited by
Cited by
Réseaux bayésiens
P Naïm, PH Wuillemin, P Leray, O Pourret, A Becker
Editions Eyrolles, 2011
Learning the structure of factored markov decision processes in reinforcement learning problems
T Degris, O Sigaud, PH Wuillemin
Proceedings of the 23rd international conference on Machine learning, 257-264, 2006
Insulin resistance and inflammation predict kinetic body weight changes in response to dietary weight loss and maintenance in overweight and obese subjects by using a Bayesian …
LC Kong, PH Wuillemin, JP Bastard, N Sokolovska, S Gougis, S Fellahi, ...
The American journal of clinical nutrition 98 (6), 1385-1394, 2013
Top-down construction and repetitive structures representation in Bayesian networks
O Bangsø, PH Wuillemin
13th Florida Artificial Intelligence Research Society Conference, 282-286, 2000
Object Oriented Bayesian Networks: A framework for top-down specification of large Bayesian networks with repetitive structures
O Bangsø, PH Wuillemin
Aalborg Universitetsforlag, 2000
aGrUM/pyAgrum: a toolbox to build models and algorithms for Probabilistic Graphical Models in Python
G Ducamp, C Gonzales, PH Wuillemin
International Conference on Probabilistic Graphical Models, 2020
Towards a global modelling of the Camembert-type cheese ripening process by coupling heterogeneous knowledge with dynamic Bayesian networks
C Baudrit, M Sicard, PH Wuillemin, N Perrot
Journal of Food Engineering 98 (3), 283-293, 2010
aGrUM: A graphical universal model framework
C Gonzales, L Torti, PH Wuillemin
Advances in Artificial Intelligence: From Theory to Practice: 30th …, 2017
Reinforcing the object-oriented aspect of probabilistic relational models
L Torti, PH Wuillemin, C Gonzales
PGM 2010-The Fifth European Workshop on Probabilistic Graphical Models, 273-280, 2010
Structured probabilistic inference
PH Wuillemin, L Torti
International Journal of Approximate Reasoning 53 (7), 946-968, 2012
Bayesian network structure learning using cooperative coevolution
O Barriàre, E Lutton, PH Wuillemin
Proceedings of the 11th Annual conference on Genetic and evolutionary …, 2009
Expert knowledge integration to model complex food processes. Application on the camembert cheese ripening process
M Sicard, C Baudrit, MN Leclerc-Perlat, PH Wuillemin, N Perrot
Expert Systems with Applications 38 (9), 11804-11812, 2011
Using ROBDDs for inference in Bayesian networks with troubleshooting as an example
TD Nielsen, PH Wuillemin, FV Jensen, U Kjærulff
arXiv preprint arXiv:1301.3880, 2013
Focused crawling through reinforcement learning
M Han, PH Wuillemin, P Senellart
Web Engineering: 18th International Conference, ICWE 2018, Cáceres, Spain …, 2018
Chi-square tests driven method for learning the structure of factored mdps
T Degris, O Sigaud, PH Wuillemin
arXiv preprint arXiv:1206.6842, 2012
Towards interactive causal relation discovery driven by an ontology
M Munch, J Dibie, PH Wuillemin, C Manfredotti
The Thirty-Second International Flairs Conference, 2019
Automation and intelligent scheduling of distributed system functional testing: Model-based functional testing in practice
LM Hillah, AP Maesano, F De Rosa, F Kordon, PH Wuillemin, R Fontanelli, ...
International journal on software tools for technology transfer 19, 281-308, 2017
Bayesian network structure learning from limited datasets through graph evolution
AP Tonda, E Lutton, R Reuillon, G Squillero, PH Wuillemin
Genetic Programming: 15th European Conference, EuroGP 2012, Málaga, Spain …, 2012
Learning probabilistic relational models using an ontology of transformation processes
M Munch, PH Wuillemin, C Manfredotti, J Dibie, S Dervaux
On the Move to Meaningful Internet Systems. OTM 2017 Conferences …, 2017
Interactive causal discovery in knowledge graphs
M Munch, J Dibie-Barthelemy, PH Wuillemin, C Manfredotti
PROFILES/SEMEX@ ISWC 2019 2465, 78-93, 2019
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