Publications on aGrUM/pyAgrum

 Gaspard Ducamp, Philippe Bonnard, Anthony Nouy, and Pierre-Henri Wuillemin. An Efficient Low-Rank Tensors Representation for Algorithms in Complex Probabilistic Graphical Models. In Probabilistic Graphical Models. Skørping, Denmark, September 2020. URL: https://hal.archives-ouvertes.fr/hal-03135705.

 Gaspard Ducamp, Philippe Bonnard, and Pierre-Henri Wuillemin. Uncertain Reasoning in Rule-Based Systems Using PRM. In FLAIRS 33 - 33rd Florida Artificial Intelligence Research Society Conference, 617–620. Miami, United States, May 2020. AAAI. URL: https://hal.archives-ouvertes.fr/hal-02612521.

 Marvin Lasserre, Régis Lebrun, and Pierre-Henri Wuillemin. Constraint-Based Learning for Non-Parametric Continuous Bayesian Networks. In FLAIRS 33 - 33rd Florida Artificial Intelligence Research Society Conference, 581–586. Miami, United States, May 2020. AAAI. URL: https://hal.archives-ouvertes.fr/hal-02615379.

 Gaspard Ducamp, Philippe Bonnard, Christian De Sainte Marie, Christophe Gonzales, and Pierre-Henri Wuillemin. Improving Probabilistic Rules Compilation using PRM. In RuleML+RR Doctoral Consortium 2018 (2nd International Joint Conference on Rules and Reasoning ). Esch-sur-Alzette, Luxembourg, September 2018. URL: https://hal.archives-ouvertes.fr/hal-01974983.

 Maria Virginia Ruiz Cuevas, Nataliya Sokolovska, Pierre-Henri Wuillemin, and Jean-Daniel Zucker. Detecting Low-Complexity Confounders from Data. In ICML / IJCAI / AAMAS FAIM'18 Workshop on CausalML. Stockholm, Sweden, July 2018. URL: https://hal .archives-ouvertes.fr/hal-01858403.

 Santiago Cortijo and Christophe Gonzales. Bayesian networks with conditional truncated densities. In Florida Artificial Intelligence Research Society Conference (FLAIRS'16), 656–661. 2016.

 Jean-Christophe Magnan and Pierre-Henri Wuillemin. Efficient Incremental Planning and Learning with Multi-Valued Decision Diagrams. Journal of Applied Logic, 2016. doi:10.1016/j.jal.2016.11.032.

 Jean-Christophe Magnan. Représentations graphiques de fonctions et processus décisionnels Markoviens factorisés. PhD thesis, University Pierre and Marie Curie, Paris, France, 2016.

 Christophe Gonzales, Séverine Dubuisson, and Cristina E. Manfredotti. A new algorithm for learning non-stationary dynamic Bayesian networks with application to event detection. In Florida Artificial Intelligence Research Society Conference (FLAIRS'15), 564–569. 2015.

 Christophe Gonzales and Séverine Dubuisson. Combinatorial Resampling Particle Filter: an Effective and Efficient Method for Articulated Object Tracking. International Journal of Computer Vision, 112(3):255–284, May 2015. URL: https://hal.archives-ouvertes.fr/hal-01170027, doi:10.1007/s11263-014-0763-z.

 Matthieu Hourbracq, Cédric Baudrit, Pierre-Henri Wuillemin, and Sebastien Destercke. Dynamic Credal Networks: introduction and use in robustness analysis. In International Symposium on Imprecise Probability: Theories and Applications (ISIPTA'13), 159–169. 2013.

 Lionel Torti, Christophe Gonzales, and Pierre-Henri Wuillemin. Speeding-up structured probabilistic inference using pattern mining. International Journal of Approximate Reasoning, 54(7):900–918, 2013.

 Lionel Torti. Structured probabilistic inference in object-oriented probabilistic graphical models. PhD thesis, University Pierre and Marie Curie, Paris, France, 2012.

 Lionel Torti, Pierre-Henri Wuillemin, and Christophe Gonzales. Reinforcing the object-oriented aspect of probabilistic relational models. In Workshop on Probabilistic Graphical Models (PGM'10), 273–280. 2010.