Sökning: "Gaussian process dynamical models"

Visar resultat 1 - 5 av 12 avhandlingar innehållade orden Gaussian process dynamical models.

1. 1. Gaussian process models of social change

   Författare :Björn Rune Helmer Blomqvist; David J. T. Sumpter; Ranjula Bali Swain; Ian Vernon; Uppsala universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Gaussian processes; Bayesian statistics; Dynamical systems; Social sciences; Tillämpad matematik och statistik; Applied Mathematics and Statistics;

   Sammanfattning : Social systems produce complex and nonlinear relationships in the indicator variables that describe them. Traditional statistical regression techniques are commonly used in the social sciences to study such systems. LÄS MER

3. 2. Probabilistic Sequence Models with Speech and Language Applications

   Författare :Gustav Eje Henter; W. Bastiaan Kleijn; Arne Leijon; Gernot Kubin; KTH; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Time series; acoustic modelling; speech synthesis; stochastic processes; causal-state splitting reconstruction; robust causal states; pattern discovery; Markov models; HMMs; nonparametric models; Gaussian processes; Gaussian process dynamical models; nonlinear Kalman filters; information theory; minimum entropy rate simplification; kernel density estimation; time-series bootstrap;

   Sammanfattning : Series data, sequences of measured values, are ubiquitous. Whenever observations are made along a path in space or time, a data sequence results. To comprehend nature and shape it to our will, or to make informed decisions based on what we know, we need methods to make sense of such data. LÄS MER

4. 3. Identification of Stochastic Nonlinear Dynamical Models Using Estimating Functions

   Författare :Mohamed Abdalmoaty; Håkan Hjalmarsson; Adrian Wills; KTH; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Prediction Error Method; Maximum Likelihood; Data-driven; Learning; Stochastic; Nonlinear; Dynamical Models; Non-stationary Linear Predictors; Intractable Likelihood; Latent Variable Models; Estimation; Process Disturbance; Electrical Engineering; Elektro- och systemteknik;

   Sammanfattning : Data-driven modeling of stochastic nonlinear systems is recognized as a very challenging problem, even when reduced to a parameter estimation problem. A main difficulty is the intractability of the likelihood function, which renders favored estimation methods, such as the maximum likelihood method, analytically intractable. 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. Bayesian learning of structured dynamical systems

   Författare :Riccardo Sven Risuleo; Håkan Hjalmarsson; Johan Schoukens; KTH; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; system identification; bayesian learning; machine learning; Gaussian processes; Electrical Engineering; Elektro- och systemteknik;

   Sammanfattning : In this thesis, we propose some Bayesian approaches to the identificationof structured dynamical systems. In particular, we consider block-orientedmodels in which a complex system is built starting from simple linear andnonlinear building blocks. LÄS MER