Belief graphical models for uncertainty representation and reasoning

DOI10.1007/978-3-030-06167-8_8zbMATH Open1547.68741MaRDI QIDQ6602255

Salem Benferhat, Karim Tabia, Philippe Leray

Publication date: 11 September 2024

Knowledge representation (68T30) Reasoning under uncertainty in the context of artificial intelligence (68T37) Probabilistic graphical models (62H22)

Cites Work

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Uncertain logical gates in possibilistic networks: theory and application to human geography
Fusion, propagation, and structuring in belief networks
The max-min hill-climbing Bayesian network structure learning algorithm
Hybrid possibilistic networks
Using inductive reasoning for completing OCF-networks
Towards scalable and data efficient learning of Markov boundaries
Graphical models for associations between variables, some of which are qualitative and some quantitative
A Bayesian method for the induction of probabilistic networks from data
Estimating the dimension of a model
The concept of a linguistic variable and its application to approximate reasoning. III
On the transformation between possibilistic logic bases and possibilistic causal networks
Bayesian network classifiers
On the logic of iterated belief revision
Bayesian belief networks for IR.
Credal networks
Towards a unified theory of imprecise probability
The naive credal classifier
CP- and OCF-networks -- a comparison
A comparative study of possibilistic conditional independence and lack of interaction
Possibilistic conditional independence: A similarity-based measure and its application to causal network learning
An introduction to variational methods for graphical models
Inference in directed evidential networks based on the transferable belief model
Compiling relational Bayesian networks for exact inference
Statistical predictor identification
Exploiting local and repeated structure in dynamic Bayesian networks
The computational complexity of probabilistic inference using Bayesian belief networks
Conditional plausibility measures and Bayesian networks
Modeling and Reasoning with Bayesian Networks
Complexity of Finding Embeddings in a k-Tree
GRAPHOID PROPERTIES OF QUALITATIVE POSSIBILISTIC INDEPENDENCE RELATIONS
10.1162/153244303321897717
Identifying independence in bayesian networks
Probabilistic Inference in Credal Networks: New Complexity Results
Approximating discrete probability distributions with dependence trees

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