Search for dissertations about: "Approximate inference"

Showing result 1 - 5 of 34 swedish dissertations containing the words Approximate inference.

  1. 1. Machine learning using approximate inference : Variational and sequential Monte Carlo methods

    Author : Christian Andersson Naesseth; Thomas Schön; Fredrik Lindsten; Iain Murray; Linköpings universitet; []

    Abstract : Automatic decision making and pattern recognition under uncertainty are difficult tasks that are ubiquitous in our everyday life. The systems we design, and technology we develop, requires us to coherently represent and work with uncertainty in data. READ MORE

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

    Author : Johan Dahlin; Thomas B. Schön; Fredrik Lindsten; Richard Everitt; Linköpings universitet; []
    Keywords : NATURAL SCIENCES; NATURVETENSKAP; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; TEKNIK OCH TEKNOLOGIER; NATURAL SCIENCES; ENGINEERING AND TECHNOLOGY; 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

  3. 3. Bayesian inference in probabilistic graphical models

    Author : Felix Leopoldo Rios; Tatjana Pavlenko; Alun Thomas; KTH; []
    Keywords : NATURAL SCIENCES; NATURVETENSKAP; 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

  4. 4. Exact inference in Bayesian networks and applications in forensic statistics

    Author : Ivar Simonsson; Chalmers University of Technology; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; familial relationship inference; Bayesian networks; exact inference; forensic statistics; variable elimination; mutation models;

    Abstract : Bayesian networks (BNs) are commonly used when describing and analyzing relationships between interacting variables. Approximate methods for performing calculations on BNs are widely used and well developed. READ MORE

  5. 5. Statistical inference with deep latent variable models

    Author : Najmeh Abiri; Beräkningsbiologi och biologisk fysik; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Deep Learning; Generative Models; Variational Inference; Missing data; Imputation; Fysicumarkivet A:2019:Abiri;

    Abstract : Finding a suitable way to represent information in a dataset is one of the fundamental problems in Artificial Intelligence. With limited labeled information, unsupervised learning algorithms help to discover useful representations. READ MORE