Dempster Specialization Matrices and the Combination of Belief Functions
ECSQARU '01 Proceedings of the 6th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Signal validation using Bayesian belief networks and fuzzy logic
Fuzzy logic and probability applications
Analyzing the combination of conflicting belief functions
Information Fusion
Editorial: Special issue in memory of Philippe Smets (1938--2005)
International Journal of Approximate Reasoning
On the Credal Structure of Consistent Probabilities
JELIA '08 Proceedings of the 11th European conference on Logics in Artificial Intelligence
International Journal of Approximate Reasoning
On the Orthogonal Projection of a Belief Function
ECSQARU '07 Proceedings of the 9th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
PRICAI '08 Proceedings of the 10th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
Quantifying beliefs by belief functions: an axiomatic justification
IJCAI'93 Proceedings of the 13th international joint conference on Artifical intelligence - Volume 1
In Memoriam: Philippe Smets (1938--2005)
Fuzzy Sets and Systems
In memoriam: Philippe Smets (1938-2005)
International Journal of Approximate Reasoning
Three alternative combinatorial formulations of the theory of evidence
Intelligent Data Analysis - Artificial Intelligence
Generating explanations for evidential reasoning
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Jeffrey's rule of conditioning generalized to belief functions
UAI'93 Proceedings of the Ninth international conference on Uncertainty in artificial intelligence
The dynamic of belief in the transferable belief model and specialization-generalization matrices
UAI'92 Proceedings of the Eighth international conference on Uncertainty in artificial intelligence
Using dempster-shafer theory in MCF systems to reject samples
MCS'05 Proceedings of the 6th international conference on Multiple Classifier Systems
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