Sökning: "Fredrik Lindsten"

Visar resultat 1 - 5 av 11 avhandlingar innehållade orden Fredrik Lindsten.

1. 1. Rao-Blackwellised particle methods for inference and identification

   Författare :Fredrik Lindsten; Thomas Schön; Lennart Ljung; Fredrik Gustafsson; Tobias Rydén; Linköpings universitet; []
   Nyckelord :TECHNOLOGY; TEKNIKVETENSKAP;

   Sammanfattning : We consider the two related problems of state inference in nonlinear dynamical systems and nonlinear system identification. More precisely, based on noisy observations from some (in general) nonlinear and/or non-Gaussian dynamical system, we seek to estimate the system state as well as possible unknown static parameters of the system. LÄS MER

3. 2. Particle filters and Markov chains for learning of dynamical systems

   Författare :Fredrik Lindsten; Thomas B. Schön; Lennart Ljung; Fredrik Gustafsson; Arnaud Doucet; Linköpings universitet; []
   Nyckelord :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;

   Sammanfattning : 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. LÄS MER

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

   Författare :Christian Andersson Naesseth; Thomas Schön; Fredrik Lindsten; Iain Murray; Linköpings universitet; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY;

   Sammanfattning : 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. LÄS MER

5. 4. Accelerating Monte Carlo methods for Bayesian inference in dynamical models

   Författare :Johan Dahlin; Thomas B. Schön; Fredrik Lindsten; Richard Everitt; Linköpings universitet; []
   Nyckelord :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;

   Sammanfattning : 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. LÄS MER

7. 5. Sequential Monte Carlo for inference in nonlinear state space models

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

   Sammanfattning : 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. LÄS MER