Avancerad sökning
Visar resultat 1 - 5 av 21 avhandlingar som matchar ovanstående sökkriterier.
1. Perspectives on Probabilistic Graphical Models
Sammanfattning : Probabilistic graphical models provide a natural framework for the representation of complex systems and offer straightforward abstraction for the interactions within the systems. Reasoning with help of probabilistic graphical models allows us to answer inference queries with uncertainty following the framework of probability theory. LÄS MER
2. Bayesian inference in probabilistic graphical models
Sammanfattning : This thesis consists of four papers studying structure learning and Bayesian inference in probabilistic graphical models for both undirected and directed acyclic graphs (DAGs).Paper A presents a novel algorithm, called the Christmas tree algorithm (CTA), that incrementally construct junction trees for decomposable graphs by adding one node at a time to the underlying graph. LÄS MER
3. Bayesian structure learning in graphical models
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. On approximations and computations in probabilistic classification and in learning of graphical models
Sammanfattning : Model based probabilistic classification is heavily used in data mining and machine learning. For computational learning these models may need approximation steps however. LÄS MER
5. Continuous time Graphical Models and Decomposition Sampling
Sammanfattning : Two topics in temporal graphical probabilistic models are studied. The topics are treated in separate papers, both with applications in finance. The first paper study inference in dynamic Bayesian networks using Monte Carlo methods. A new method for sampling random variables is proposed. LÄS MER