Search for dissertations about: "approximate bayesian computations"
Showing result 1 - 5 of 6 swedish dissertations containing the words approximate bayesian computations.
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1. Accelerating Monte Carlo methods for Bayesian inference in dynamical models
Abstract : Making decisions and predictions from noisy observations are two important and challenging problems in many areas of society. Some examples of applications are recommendation systems for online shopping and streaming services, connecting genes with certain diseases and modelling climate change. READ MORE
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2. Computational Modeling, Parameterization, and Evaluation of the Spread of Diseases
Abstract : Computer simulations play a vital role in the modeling of infectious diseases. Different modeling regimes fit specific purposes, from ordinary differential equations to probabilistic formulations. READ MORE
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3. Bayesian inference in probabilistic graphical models
Abstract : 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. READ MORE
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4. Sequential Monte Carlo for inference in nonlinear state space models
Abstract : Nonlinear state space models (SSMs) are a useful class of models to describe many different kinds of systems. Some examples of its applications are to model; the volatility in financial markets, the number of infected persons during an influenza epidemic and the annual number of major earthquakes around the world. READ MORE
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5. Spatial inference for non-lattice data using Markov Random fields
Abstract : This thesis deals with how computationally effective lattice models could be used for inference of data with a continuous spatial index. The fundamental idea is to approximate a Gaussian field with a Gaussian Markov random field (GMRF) on a lattice. READ MORE