Towards a global modelling of the Camembert-type cheese ripening process by coupling heterogeneous knowledge with dynamic Bayesian networks, Journal of Food Engineering, vol.98, issue.3, pp.283-293, 2010. ,
DOI : 10.1016/j.jfoodeng.2009.12.012
URL : https://hal.archives-ouvertes.fr/hal-01170294
Parameter elicitation in probabilistic graphical models for modelling multi-scale food complex systems, Journal of Food Engineering, vol.115, issue.1, pp.1-10, 2013. ,
DOI : 10.1016/j.jfoodeng.2012.09.012
URL : https://hal.archives-ouvertes.fr/hal-01001573
Hybrid possibilistic networks, International Journal of Approximate Reasoning, vol.44, issue.3, pp.224-243, 2007. ,
DOI : 10.1016/j.ijar.2006.07.012
URL : https://hal.archives-ouvertes.fr/hal-00191096
Sensitivity analysis for probability assessments in bayesian networks, Proceedings of the Ninth international conference on Uncertainty in artificial intelligence, UAI'93, pp.136-142, 1993. ,
A guide to the literature on learning probabilistic networks from data. Knowledge and Data Engineering, IEEE Transactions on, vol.8, issue.2, pp.195-210, 1996. ,
Convex sets of probabilities propagation by simulated annealing on a tree of cliques, In: Proceedings of Fifth International Conference on Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU '94, pp.4-8, 1994. ,
Hill-climbing and branch-and-bound algorithms for exact and approximate inference in credal networks, International Journal of Approximate Reasoning, vol.44, issue.3, pp.261-280, 2007. ,
DOI : 10.1016/j.ijar.2006.07.020
A genetic algorithm to approximate convex sets of probabilities, Proc. of the Int. Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, pp.859-864, 1996. ,
Using probability trees to compute marginals with imprecise probabilities, International Journal of Approximate Reasoning, vol.29, issue.1, pp.1-46, 2002. ,
DOI : 10.1016/S0888-613X(01)00046-9
Sensitivity analysis in discrete Bayesian networks, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, vol.27, issue.4, pp.412-423, 1997. ,
DOI : 10.1109/3468.594909
Sensitivity analysis in bayesian networks: From single to multiple parameters, Proceedings of the 20'th international Conference on Uncertainty in Artificial Intelligence, UAI'04, 2004. ,
On the revision of probabilistic beliefs using uncertain evidence, Artificial Intelligence, vol.163, issue.1, pp.67-90, 2005. ,
DOI : 10.1016/j.artint.2004.09.005
Sensitivity analysis for threshold decision making with dynamic networks, Proceedings of the Twenty-Second Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-06), pp.72-79, 2006. ,
Properties of sensitivity analysis of bayesian belief networks, Proceedings of the Joint Session of the 6th Prague Symposium of Asymptotic Statistics and the 13th Prague Conference on Information Theory , Statistical Decision Functions and Random Processes of Czech Mathematicians and Physicists, pp.81-86, 1999. ,
A survey of concepts of independence for imprecise probabilities, Risk Decision and Policy, vol.5, issue.2, pp.165-181, 2000. ,
DOI : 10.1017/S1357530900000156
Robustness analysis of bayesian networks with local convex sets of distributions, Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence, UAI'97, pp.108-115, 1997. ,
Credal networks, Artificial Intelligence, vol.120, issue.2, pp.199-233, 2000. ,
DOI : 10.1016/S0004-3702(00)00029-1
Separation properties of sets of probability measures Cozman. Graphical models for imprecise probabilities, Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence, pp.107-114167, 2000. ,
Inference with separately specified sets of probabilities in credal networks, Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence, UAI'02, pp.430-437, 2002. ,
Inference in polytrees with sets of probabilities, Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence, UAI'03, pp.217-224, 2003. ,
State sequence prediction in imprecise hidden markov models, Proceedings of the seventh International Symposium on Imprecise Probabilities: Theory and Applications, pp.159-168, 2011. ,
Inference in credal networks using multilinear programming, Proceedings of the 2nd Starting AI Researchers' Symposium, pp.50-61, 2004. ,
Inference in credal networks through integer programming, Proceedings of the 5th International Symposium on Imprecise Probability: Theories and Applications, pp.145-154, 2007. ,
PROBABILITY INTERVALS: A TOOL FOR UNCERTAIN REASONING, Fuzziness and Knowledge-Based Systems, pp.167-196, 1994. ,
DOI : 10.1142/S0218488594000146
Representing and solving factored markov decision processes with imprecise probabilities, Proceedings ISIPTA, pp.169-178, 2009. ,
2U: an exact interval propagation algorithm for polytrees with binary variables, Artificial Intelligence, vol.106, issue.1, pp.77-107, 1998. ,
DOI : 10.1016/S0004-3702(98)00089-7
Cheese -Chemistry, Physics and Microbiology, 2004. ,
Monte carlo methods. Encyclopedia of Statistical Sciences, 2006. ,
Approximate Inference in Credal Networks by Variational Mean Field Methods, International Symposium on Imprecise Probabilities and Their Applications, pp.203-212, 2005. ,
Approximate algorithms for credal networks with binary variables, International Journal of Approximate Reasoning, vol.48, issue.1, pp.275-296, 2008. ,
DOI : 10.1016/j.ijar.2007.09.003
Ipe and l2u: Approximate algorithms for credal networks, Proceedings of the second starting AI Researcher Symposium, pp.118-127, 2004. ,
Van der Gaag. The computational complexity of sensitivity analysis and parameter tuning, Proceedings of the 24th Conference in Uncertainty in Artificial Intelligence, pp.349-356, 2008. ,
The EM algorithm for graphical association models with missing data, Computational Statistics & Data Analysis, vol.19, issue.2, pp.191-201, 1995. ,
DOI : 10.1016/0167-9473(93)E0056-A
The Enterprise of Knowledge: An Essay on Knowledge, Credal Probobility, and Chance, 1983. ,
Dynamic Bayesian networks: representation , inference and learning, 2002. ,
Bayesian networks and decision graphs, 2007. ,
Probabilistic reasoning in intelligent systems: networks of plausible inference, 1988. ,
Modelling and analysis of complex food systems: State of the art and new trends, Trends in Food Science & Technology, vol.22, issue.6, pp.304-314, 2011. ,
DOI : 10.1016/j.tifs.2011.03.008
URL : https://hal.archives-ouvertes.fr/hal-01000973
A tutorial on hidden markov models and selected applications in speech recognition, Proceedings of the IEEE, pp.257-286, 1989. ,
The Logic of Decision, 1983. ,
Evidence Propagation in Credal Networks: An Exact Algorithm Based on Separately Specified Sets of Probability, Advances in Artificial Intelligence, pp.376-385, 2002. ,
DOI : 10.1007/3-540-36127-8_36
Making sensitivity analysis computationally efficient, Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence, UAI'00, pp.317-325, 2000. ,
Statistical reasoning with imprecise probabilities, 1991. ,
DOI : 10.1007/978-1-4899-3472-7
Reasoning in evidential networks with conditional belief functions, International Journal of Approximate Reasoning, vol.14, issue.2-3, pp.155-185, 1996. ,
DOI : 10.1016/0888-613X(96)00113-2
Generalized belief propagation, NIPS 13, pp.689-695, 2000. ,