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Showing result 1 - 5 of 160 swedish dissertations matching the above criteria.

2. 1. Accelerating Monte Carlo methods for Bayesian inference in dynamical models

   Author : Johan Dahlin; Thomas B. Schön; Fredrik Lindsten; Richard Everitt; Linköpings universitet; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; Computational statistics; Monte Carlo; Markov chains; Particle filters; Machine learning; Bayesian optimisation; Approximate Bayesian Computations; Gaussian processes; Particle Metropolis-Hastings; Approximate inference; Pseudo-marginal methods;

   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

4. 2. On flexible random field models for spatial statistics: Spatial mixture models and deformed SPDE models

   Author : Anders Hildeman; Chalmers tekniska högskola; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Spatial statistics; Significant wave height; Spatial mixture model; Stochastic partial differential equation; Log-Gaussian Cox process; Point process; Gaussian random field; Substitute-CT;

   Abstract : Spatial random fields are one of the key concepts in statistical analysis of spatial data. The random field explains the spatial dependency and serves the purpose of regularizing interpolation of measured values or to act as an explanatory model. READ MORE

5. 3. Computational Aspects of Lévy-Driven SPDE Approximations

   Author : Andreas Petersson; Göteborgs universitet; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; multilevel Monte Carlo; numerical approximation of stochastic differential equations; multiplicative noise; Lévy processes; finite element method; variance redons; Monte Carlo; weak convergence; Lévy processes;

   Abstract : In order to simulate solutions to stochastic partial differential equations (SPDE) they must be approximated in space and time. In this thesis such fully discrete approximations are considered, with an emphasis on finite element methods combined with rational semigroup approximations. There are several notions of the error resulting from this. READ MORE

6. 4. Computational Modeling, Parameterization, and Evaluation of the Spread of Diseases

   Author : Robin Marin; Stefan Engblom; Trevelyan J. McKinley; Uppsala universitet; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Parameter estimation; Bayesian modeling; Stochastic epidemiological models; simulation-based inference; approximate bayesian computations; Scientific Computing; Beräkningsvetenskap;

   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

7. 5. The PET sampling puzzle : intelligent data sampling methods for positron emission tomography

   Author : Klara Leffler; Jun Yu; Ida Häggström; Zhiyong Zhou; Saikat Chatterjee; Umeå universitet; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; sparse signal processing; compressed sensing; Poisson denoising; positron emission tomography PET ; sinogram denoising; sinogram inpainting; deep learning; matematisk statistik; Mathematical Statistics;

   Abstract : Much like a backwards computed Sudoku puzzle, starting from the completed number grid and working ones way down to a partially completed grid without damaging the route back to the full unique solution, this thesis tackles the challenges behind setting up a number puzzle in the context of biomedical imaging. By leveraging sparse signal processing theory, we study the means of practical undersampling of positron emission tomography (PET) measurements, an imaging modality in nuclear medicine that visualises functional processes within the body using radioactive tracers. READ MORE