Search for dissertations about: "Particle MCMC"

Showing result 1 - 5 of 6 swedish dissertations containing the words Particle MCMC.

  2. 1. 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

  4. 2. Inverse Modeling of Cloud – Aerosol Interactions

    Author : Daniel Partridge; Johan Ström; Kari Lehtinen; Stockholms universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; stratocumulus; marine; cloud; aerosol; interactions; MCMC; inverse modeling; droplet closure; global sensitivity; Atmosphere and hydrosphere sciences; Atmosfärs- och hydrosfärsvetenskap; Applied Environmental Science; tillämpad miljövetenskap;

    Abstract : The role of aerosols and clouds is one of the largest sources of uncertainty in understanding climate change. The primary scientific goal of this thesis is to improve the understanding of cloud-aerosol interactions by applying inverse modeling using Markov Chain Monte Carlo (MCMC) simulation. READ MORE

  5. 3. 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

  6. 4. 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

  7. 5. Recursive Bayesian Estimation : Navigation and Tracking Applications

    Author : Niclas Bergman; Fredrik Gustafsson; Lennart Ljung; Linköpings universitet; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Target tracking; Autonomous aircraft navigation; Terrain navigation;

    Abstract : Recursive estimation deals with the problem of extracting information about parameters, or states, of a dynamical system in real time, given noisy measurements of the system output. Recursive estimation plays a central role in many applications of signal processing, system identification and automatic control. READ MORE