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1. 1. Gated Bayesian Networks

   Författare :Marcus Bendtsen; Jose M. Peña; Nahid Shahmehri; Helge Langseth; Linköpings universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES;

   Sammanfattning : Bayesian networks have grown to become a dominant type of model within the domain of probabilistic graphical models. Not only do they empower users with a graphical means for describing the relationships among random variables, but they also allow for (potentially) fewer parameters to estimate, and enable more efficient inference. LÄS MER

3. 2. Bayesian structure learning in graphical models

   Författare :Felix Leopoldo Rios; Tatjana Pavlenko; Klas Markström; KTH; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Bayesian statistics; graphical models; Bayesian networks; Markov networks; structure learning; Tillämpad matematik och beräkningsmatematik; Applied and Computational Mathematics;

   Sammanfattning : This thesis consists of two papers studying structure learning in probabilistic graphical models for both undirected graphs anddirected acyclic graphs (DAGs).Paper A, presents a novel family of graph theoretical algorithms, called the junction tree expanders, that incrementally construct junction trees for decomposable graphs. LÄS MER

4. 3. Essays on Bayesian Inference for Social Networks

   Författare :Johan Koskinen; Ove Frank; Philippa Pattison; Stockholms universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Bayesian inference; social network analysis; Markov chain Monte Carlo; exponential random graphs; cognitive social structures; longitudinal social networks.; Statistics; Statistik;

   Sammanfattning : This thesis presents Bayesian solutions to inference problems for three types of social network data structures: a single observation of a social network, repeated observations on the same social network, and repeated observations on a social network developing through time.A social network is conceived as being a structure consisting of actors and their social interaction with each other. LÄS MER

5. 4. Bayesian Models for Spatiotemporal Data from Transportation Networks

   Författare :Héctor Rodriguez Déniz; Mattias Villani; Augusto Voltes-Dorta; Yusak Susilo; Linköpings universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Bayesian statistics; Transportation networks; Spatiotemporal data; Machine learning; Bayesiansk statistik; Transportnätverk; Spatiotemporal data; Maskininlärning;

   Sammanfattning : Urbanization has caused a historical transformation at a global scale, and humanity is moving towards a fully connected society where cities will concentrate population, infrastructure and economic activity. A key element in the cities’ infrastructure is the transportation system, as it facilitates the mobility of people and goods. LÄS MER

7. 5. Bayesian networks: exact inference and applications in forensic statistics

   Författare :Ivar Simonsson; Göteborgs universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Bayesian networks; variable elimination algorithm; forensic statistics; relationship inference; mutation models; relationship inference;

   Sammanfattning : Exact inference on Bayesian networks has been developed through sophisticated algorithms. One of which, the variable elimination algorithm, identifies smaller components of the network, called factors, on which local operations are performed. In principle this algorithm can be used on any Bayesian network. LÄS MER