Sökning: "mattias villani"

Visar resultat 6 - 10 av 16 avhandlingar innehållade orden mattias villani.

1. 6. Bayesian Modeling of Conditional Densities

   Författare :Feng Li; Mattias Villani; Sylvia Frühwirth-Schnatter; Stockholms universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Bayesian inference; Density estimation; smooth mixtures; surface regression; copulas; Markov chain Monte Carlo; Statistics; statistik;

   Sammanfattning : This thesis develops models and associated Bayesian inference methods for flexible univariate and multivariate conditional density estimation. The models are flexible in the sense that they can capture widely differing shapes of the data. The estimation methods are specifically designed to achieve flexibility while still avoiding overfitting. LÄS MER

3. 7. Scalable and Efficient Probabilistic Topic Model Inference for Textual Data

   Författare :Måns Magnusson; Mattias Villani; Marco Kuhlmann; Jordan Boyd-Graber; Linköpings universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Text analysis; Bayesian inference; Markov chain Monte Carlo; topic models; Textanalys; Bayesiansk inferens; Markov chain Monte Carlo; temamodeller;

   Sammanfattning : Probabilistic topic models have proven to be an extremely versatile class of mixed-membership models for discovering the thematic structure of text collections. There are many possible applications, covering a broad range of areas of study: technology, natural science, social science and the humanities. LÄS MER

4. 8. Bayesian Sequential Inference for Dynamic Regression Models

   Författare :Parfait Munezero; Mattias Villani; Helga Wagner; Stockholms universitet; []
   Nyckelord :SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; Bayesian sequential inference; Dynamic regression models; Particle filter; Online prediction; Particle smoothing; Linear Bayes; Statistics; statistik;

   Sammanfattning : Many processes evolve over time and statistical models need to be adaptive to change. This thesis proposes flexible models and statistical methods for inference about a data generating process that varies over time. The models considered are quite general dynamic predictive models with parameters linked to a set of covariates via link functions. LÄS MER

5. 9. Learning local predictive accuracy for expert evaluation and forecast combination

   Författare :Oscar Oelrich; Mattias Villani; Francesco Ravazzolo; Stockholms universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Bayesian; forecast combination; predictive density; Gaussian process; bootstrap; Bayes factors; model selection; Bayesian predictive synthesis; nonparametric methods; power transformation; expected log predictive density; variable selection; statistik; Statistics;

   Sammanfattning : This thesis consists of four papers that study several topics related to expert evaluation and aggregation. Paper I explores the properties of Bayes factors. Bayes factors, which are used for Bayesian hypothesis testing as well as to aggregate models using Bayesian model averaging, are sometimes observed to behave erratically. LÄS MER

7. 10. Machine learning for spatially varying data

   Författare :Muhammad Osama; Dave Zachariah; Mattias Villani; Uppsala universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Machine learning; spatio-temporal; spatial; Electrical Engineering with specialization in Signal Processing; Elektroteknik med inriktning mot signalbehandling;

   Sammanfattning : Many physical quantities around us vary across space or space-time. An example of a spatial quantity is provided by the temperature across Sweden on a given day and as an example of a spatio-temporal quantity we observe the counts of the corona virus cases across the globe. LÄS MER