Wafa Laâmari

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The temporal dimension is a very important aspect which must be taken into account when reasoning under uncertainty. The main purpose of this paper is to address this problem by a new evi-dential framework for modeling temporal changes in data. This method, allowing to model uncertainty and to manage time varying information thanks to the evidence theory,(More)
A wide variety of compilation techniques have been proposed in the literature for inference in static graphical models. One of the most widely used approaches is the arithmetic circuit method. Compiling a graphical model into an arithmetic circuit provides a compact representation of the polynomial that it induces. This representation allows linear time(More)
Directed evidential graphical models are important tools for handling uncertain information in the framework of evidence theory. They obtain their efficiency by compactly representing (in)dependencies between variables in the network and efficiently reasoning under uncertainty. This paper presents a new dynamic evidential network for representing(More)
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