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Visar resultat 1 - 5 av 20 avhandlingar som matchar ovanstående sökkriterier.
1. Bayesian Cluster Analysis : Some Extensions to Non-standard Situations
Sammanfattning : The Bayesian approach to cluster analysis is presented. We assume that all data stem from a finite mixture model, where each component corresponds to one cluster and is given by a multivariate normal distribution with unknown mean and variance. LÄS MER
2. Physics-informed inferences of galaxy clustering with Bayesian forward modelling
Sammanfattning : In this thesis, we showcase four novel approaches to constraining the relationship between cosmological observables and the large-scale structure. The majority of the energy content of the Universe in the concordance cosmological model remains largely unknown. LÄS MER
3. Bayesian Modeling of Directional Data with Acoustic and Other Applications
Sammanfattning : A direction is defined here as a multi-dimensional unit vector. Such unitvectors form directional data. Closely related to directional data are axialdata for which each direction is equivalent to the opposite direction.Directional data and axial data arise in various fields of science. LÄS MER
4. Approximations of Bayes Classifiers for Statistical Learning of Clusters
Sammanfattning : It is rarely possible to use an optimal classifier. Often the classifier used for a specific problem is an approximation of the optimal classifier. Methods are presented for evaluating the performance of an approximation in the model class of Bayesian Networks. LÄS MER
5. Statistical and machine learning methods to analyze large-scale mass spectrometry data
Sammanfattning : Modern biology is faced with vast amounts of data that contain valuable information yet to be extracted. Proteomics, the study of proteins, has repositories with thousands of mass spectrometry experiments. These data gold mines could further our knowledge of proteins as the main actors in cell processes and signaling. LÄS MER