Search for dissertations about: "markov chain monte carlo mcmc"

Showing result 1 - 5 of 37 swedish dissertations containing the words markov chain monte carlo mcmc.

2. 1. Markov Chain Monte Carlo Methods and Applications in Neuroscience

   Author : Federica Milinanni; Pierre Nyquist; Mark Clements; KTH; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; Markov chain Monte Carlo; Large deviations; Subcellular pathway models; Markov chain Monte Carlo; Stora avvikelser; Subcellular pathway models; Tillämpad matematik och beräkningsmatematik; Applied and Computational Mathematics;

   Abstract : An important task in brain modeling is that of estimating model parameters and quantifying their uncertainty. In this thesis we tackle this problem from a Bayesian perspective: we use experimental data to update the prior information about model parameters, in order to obtain their posterior distribution. READ MORE

4. 2. 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

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. Rare-event simulation with Markov chain Monte Carlo

   Author : Thorbjörn Gudmundsson; Henrik Hult; Ad Ridder; KTH; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; Tillämpad matematik och beräkningsmatematik; Applied and Computational Mathematics;

   Abstract : Stochastic simulation is a popular method for computing probabilities or expecta- tions where analytical answers are difficult to derive. It is well known that standard methods of simulation are inefficient for computing rare-event probabilities and there- fore more advanced methods are needed to those problems. READ MORE

7. 5. Correct and Efficient Monte Carlo Inference for Universal Probabilistic Programming Languages

   Author : Daniel Lundén; David Broman; Lawrence Murray; Joakim Jaldén; Sam Staton; KTH; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; Probabilistic programming languages; Compilers; Static program analysis; Monte Carlo inference; Operational semantics; Probabilistiska programmeringsspråk; Kompilatorer; Statisk programanalys; Monte Carlo-inferens; Operationell semantik; Informations- och kommunikationsteknik; Information and Communication Technology;

   Abstract : Probabilistic programming languages (PPLs) allow users to express statistical inference problems that the PPL implementation then, ideally, solves automatically. In particular, PPL users can focus on encoding their inference problems, and need not concern themselves with the intricacies of inference. READ MORE