Search for dissertations about: "sequential sampling"

Showing result 16 - 20 of 44 swedish dissertations containing the words sequential sampling.

  2. 16. Sequential Monte Carlo Methods with Applications to Positioning and Tracking in Wireless Networks

    Author : Svetlana Bizjajeva; Matematisk statistik; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; positioning; state-space models; SMCM; particle filtering;

    Abstract : This thesis is based on 5 papers exploring the filtering problem in non-linear non-Gaussian state-space models together with applications of Sequential Monte Carlo (also called particle filtering) methods to the positioning in wireless networks. The aim of the first paper is to study the performance of particle filtering techniques in mobile positioning using signal strength measurements. READ MORE

  4. 17. Simulation-based Inference : From Approximate Bayesian Computation and Particle Methods to Neural Density Estimation

    Author : Samuel Wiqvist; Matematisk statistik; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Bayesian statistics; computational statistics; deep learning; mixed­-effects; sequential Monte Carlo; stochastic dif­ferential equations;

    Abstract : This doctoral thesis in computational statistics utilizes both Monte Carlo methods(approximate Bayesian computation and sequential Monte Carlo) and machine­-learning methods (deep learning and normalizing flows) to develop novel algorithms for infer­ence in implicit Bayesian models. Implicit models are those for which calculating the likelihood function is very challenging (and often impossible), but model simulation is feasible. READ MORE

  5. 18. Particle filters and Markov chains for learning of dynamical systems

    Author : Fredrik Lindsten; Thomas B. Schön; Lennart Ljung; Fredrik Gustafsson; Arnaud Doucet; Linköpings universitet; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; Bayesian learning; System identification; Sequential Monte Carlo; Markov chain Monte Carlo; Particle MCMC; Particle filters; Particle smoothers;

    Abstract : Sequential Monte Carlo (SMC) and Markov chain Monte Carlo (MCMC) methods provide computational tools for systematic inference and learning in complex dynamical systems, such as nonlinear and non-Gaussian state-space models. This thesis builds upon several methodological advances within these classes of Monte Carlo methods. READ MORE

  6. 19. Capillary driven devices for patient-centric diagnostics

    Author : Gabriel Lenk; Niclas Roxhed; Göran Stemme; Jens Ducrée; KTH; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Capillary driven; Microfluidic; Dissolvable valves; PVA; Volume metering; Dried Blood Spots; DBS; Dried Plasma Spots; DPS; Medicinsk teknologi; Medical Technology;

    Abstract : Lateral flow assays is an example of a successful microfluidic platform relying on passive fluid transport, making them suitable for patient-centric and point-of-care applications. Flow control and valving in capillary driven devices typically rely on design-imprinted functions and operations which can be a limiting factor. READ MORE

  7. 20. Bayesian structure learning in graphical models

    Author : Felix Leopoldo Rios; Tatjana Pavlenko; Klas Markström; KTH; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Bayesian statistics; graphical models; Bayesian networks; Markov networks; structure learning; Tillämpad matematik och beräkningsmatematik; Applied and Computational Mathematics;

    Abstract : 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. READ MORE