Search for dissertations about: "Approximate Bayesian Computations"

Showing result 1 - 5 of 6 swedish dissertations containing the words Approximate Bayesian Computations.

  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. 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

  5. 3. Bayesian inference in probabilistic graphical models

    Author : Felix Leopoldo Rios; Tatjana Pavlenko; Alun Thomas; KTH; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Graphical models; Bayesian inference; predictive classification; decomposable graphs; Tillämpad matematik och beräkningsmatematik; Applied and Computational Mathematics;

    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

  6. 4. Sequential Monte Carlo for inference in nonlinear state space models

    Author : Johan Dahlin; Thomas Schön; Fredrik Lindsten; Adam M. Johansen; Linköpings universitet; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY;

    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

  7. 5. Spatial inference for non-lattice data using Markov Random fields

    Author : Linda Werner Hartman; Matematisk statistik; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES;

    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